INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91251, 2007, 'bmc', 'IDconverter and IDClight: conversion and annotation of gene and protein IDs', 'Alibés, Andreu|Yankilevich, Patricio|Cañada, Andrés|Díaz-Uriarte, Ramón', 'Structural Biology and Biocomputing Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro 3, 28029, Madrid, Spain. aalibes@gmail.com|Structural Biology and Biocomputing Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro 3, 28029, Madrid, Spain. aalibes@gmail.com|Structural Biology and Biocomputing Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro 3, 28029, Madrid, Spain. aalibes@gmail.com|Structural Biology and Biocomputing Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro 3, 28029, Madrid, Spain. aalibes@gmail.com', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Genes|Information Storage and Retrieval|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Proteins|Software|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-8-9', '17214880', 'Researchers involved in the annotation of large numbers of gene, clone or protein identifiers are usually required to perform a one-by-one conversion for each identifier. When the field of research is one such as microarray experiments, this number may be around 30,000.'),
(91252, 2007, 'bmc', 'Bioinformatics analysis of the early inflammatory response in a rat thermal injury model', 'Yang, Eric|Maguire, Timothy|Yarmush, Martin L|Berthiaume, Francois|Androulakis, Ioannis P', 'Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. eyang@eden.rutgers.edu <eyang@eden.rutgers.edu>|Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. eyang@eden.rutgers.edu <eyang@eden.rutgers.edu>|Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. eyang@eden.rutgers.edu <eyang@eden.rutgers.edu>|Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. eyang@eden.rutgers.edu <eyang@eden.rutgers.edu>|Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. eyang@eden.rutgers.edu <eyang@eden.rutgers.edu>', 'United States|United States|United States|United States|United States', 24, 'Algorithms|Animals|Burns|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Hot Temperature|Inflammation|Male|Models, Statistical|Oligonucleotide Array Sequence Analysis|Rats|Rats, Sprague-Dawley|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-10', '17214898', 'Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities.'),
(91253, 2006, 'bmc', 'Development of computations in bioscience and bioinformatics and its application: review of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06)', 'Deng, Youping|Ni, Jun|Zhang, Chaoyang', 'Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. youping.deng@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. youping.deng@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. youping.deng@usm.edu', 'United States|United States|United States', 1, 'Biological Science Disciplines|Biology|Computational Biology|Gene Expression Profiling|Genomics', 'Congress', '10.1186/1471-2105-7-S4-S1', '17217501', 'The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21-22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.'),
(91254, 2006, 'bmc', 'SEQOPTICS: a protein sequence clustering system', 'Chen, Yonghui|Reilly, Kevin D|Sprague, Alan P|Guan, Zhijie', 'Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL 35294-1170, USA. chenyh@cis.uab.edu|Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL 35294-1170, USA. chenyh@cis.uab.edu|Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL 35294-1170, USA. chenyh@cis.uab.edu|Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL 35294-1170, USA. chenyh@cis.uab.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-S4-S10', '17217502', 'Protein sequence clustering has been widely used as a part of the analysis of protein structure and function. In most cases single linkage or graph-based clustering algorithms have been applied. OPTICS (Ordering Points To Identify the Clustering Structure) is an attractive approach due to its emphasis on visualization of results and support for interactive work, e.g., in choosing parameters. However, OPTICS has not been used, as far as we know, for protein sequence clustering.'),
(91255, 2006, 'bmc', 'The relationship between protein sequences and their gene ontology functions', 'Duan, Zhong-Hui|Hughes, Brent|Reichel, Lothar|Perez, Dianne M|Shi, Ting', 'Department of Computer Science, University of Akron, Akron, OH 44325, USA. duan@uakron.edu|Department of Computer Science, University of Akron, Akron, OH 44325, USA. duan@uakron.edu|Department of Computer Science, University of Akron, Akron, OH 44325, USA. duan@uakron.edu|Department of Computer Science, University of Akron, Akron, OH 44325, USA. duan@uakron.edu|Department of Computer Science, University of Akron, Akron, OH 44325, USA. duan@uakron.edu', 'United States|United States|United States|United States|United States', 0, 'Amino Acid Sequence|Molecular Sequence Data|Phylogeny|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Statistics as Topic|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S11', '17217503', 'One main research challenge in the post-genomic era is to understand the relationship between protein sequences and their biological functions. In recent years, several automated annotation systems have been developed for the functional assignment of uncharacterized proteins. The underlying assumption of these systems is that similar sequences imply similar biological functions. However, it has been noted that matching sequences do not always infer similar functions.'),
(91256, 2006, 'bmc', 'Towards a better solution to the shortest common supersequence problem: the deposition and reduction algorithm', 'Ning, Kang|Leong, Hon Wai', 'Department of Computer Science, National University of Singapore, Science Drive, Singapore 117543, Singapore. ningkang@comp.nus.edu.sg|Department of Computer Science, National University of Singapore, Science Drive, Singapore 117543, Singapore. ningkang@comp.nus.edu.sg', 'Singapore|Singapore', 0, 'Algorithms|Conserved Sequence|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S12', '17217504', 'The problem of finding a Shortest Common Supersequence (SCS) of a set of sequences is an important problem with applications in many areas. It is a key problem in biological sequences analysis. The SCS problem is well-known to be NP-complete. Many heuristic algorithms have been proposed. Some heuristics work well on a few long sequences (as in sequence comparison applications), others work well on many short sequences (as in oligo-array synthesis). Unfortunately, most do not work well on large SCS instances where there are many, long sequences.'),
(91257, 2006, 'bmc', 'Determination of the minimum number of microarray experiments for discovery of gene expression patterns', 'Wu, Fang-Xiang|Zhang, W J|Kusalik, Anthony J', 'Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada. faw341@mail.usask.ca|Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada. faw341@mail.usask.ca|Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada. faw341@mail.usask.ca', 'Canada|Canada|Canada', 3, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Data Interpretation, Statistical|Discriminant Analysis|Gene Expression|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sample Size', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S13', '17217505', 'One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two important issues with such an experiment are the number of time points, and the interval between them. In the absence of biological knowledge regarding appropriate values, it is natural to question whether the behaviour of progressively generated data may by itself determine a threshold beyond which further microarray experiments do not contribute to pattern discovery. Additionally, such a threshold implies a minimum number of microarray experiments, which is important given the cost of these experiments.'),
(91258, 2006, 'bmc', 'Improved Chou-Fasman method for protein secondary structure prediction', 'Chen, Hang|Gu, Fei|Huang, Zhengge', 'Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310027, China. ch-sun@263.net|Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310027, China. ch-sun@263.net|Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310027, China. ch-sun@263.net', 'China|China|China', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Hydrophobic and Hydrophilic Interactions|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S14', '17217506', 'Protein secondary structure prediction is a fundamental and important component in the analytical study of protein structure and functions. The prediction technique has been developed for several decades. The Chou-Fasman algorithm, one of the earliest methods, has been successfully applied to the prediction. However, this method has its limitations due to low accuracy, unreliable parameters, and over prediction. Thanks to the recent development in protein folding type-specific structure propensities and wavelet transformation, the shortcomings in Chou-Fasman method are able to be overcome.'),
(91259, 2006, 'bmc', 'Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data', 'Zhang, Chaoyang|Li, Peng|Rajendran, Arun|Deng, Youping|Chen, Dequan', 'School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. chaoyang.zhang@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. chaoyang.zhang@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. chaoyang.zhang@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. chaoyang.zhang@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. chaoyang.zhang@usm.edu', 'United States|United States|United States|United States|United States', 14, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Computing Methodologies|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S15', '17217507', 'Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the process of generating models in traditional multicategory support vector machines for large datasets is very computationally intensive, there is a need to improve the performance using high performance computing techniques.'),
(91260, 2006, 'bmc', 'Identification of new members of hydrophobin family using primary structure analysis', 'Yang, Kuan|Deng, Youping|Zhang, Chaoyang|Elasri, Mohamed', 'Department of Biological Sciences, University of SouthernMississippi, Hattiesburg, Mississippi 39406, USA. kuan.yang@usm.edu|Department of Biological Sciences, University of SouthernMississippi, Hattiesburg, Mississippi 39406, USA. kuan.yang@usm.edu|Department of Biological Sciences, University of SouthernMississippi, Hattiesburg, Mississippi 39406, USA. kuan.yang@usm.edu|Department of Biological Sciences, University of SouthernMississippi, Hattiesburg, Mississippi 39406, USA. kuan.yang@usm.edu', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Animals|Conserved Sequence|Fungal Proteins|Humans|Molecular Sequence Data|Multigene Family|Phylogeny|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S16', '17217508', 'Hydrophobins are fungal proteins that can turn into amphipathic membranes at hydrophilic/hydrophobic interfaces by self-assembly. The assemblages by Class I hydrophobins are extremely stable and possess the remarkable ability to change the polarity of the surface. One of its most important industrial applications is its usage as paint. Without detailed knowledge of the 3D structure and self-assembly principles of hydrophobins, it is difficult to make significant progress in furthering its research.'),
(91261, 2006, 'bmc', 'Evaluation of clustering algorithms for gene expression data', 'Datta, Susmita|Datta, Somnath', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA. susmita.datta@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA. susmita.datta@louisville.edu', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-7-S4-S17', '17217509', 'Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped together according to their expression profiles using one of numerous clustering algorithms that exist in the statistics and machine learning literature. A closely related problem is that of selecting a clustering algorithm that is optimal in some sense from a rather impressive list of clustering algorithms that currently exist.'),
(91262, 2006, 'bmc', 'GenomeBlast: a web tool for small genome comparison', 'Lu, Guoqing|Jiang, Liying|Helikar, Resa M K|Rowley, Thaine W|Zhang, Luwen|Chen, Xianfeng|Moriyama, Etsuko N', 'Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA. glu3@mail.unomaha.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Databases, Genetic|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S18', '17217510', 'Comparative genomics has become an essential approach for identifying homologous gene candidates and their functions, and for studying genome evolution. There are many tools available for genome comparisons. Unfortunately, most of them are not applicable for the identification of unique genes and the inference of phylogenetic relationships in a given set of genomes.'),
(91263, 2006, 'bmc', 'Clustering of gene expression data: performance and similarity analysis', 'Yin, Longde|Huang, Chun-Hsi|Ni, Jun', 'Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA. yin@engr.uconn.edu|Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA. yin@engr.uconn.edu|Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA. yin@engr.uconn.edu', 'United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-7-S4-S19', '17217511', 'DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expression. Many clustering algorithms have been proposed to analyze gene expression data, but little guidance is available to help choose among them. The evaluation of feasible and applicable clustering algorithms is becoming an important issue in todays bioinformatics research.'),
(91264, 2006, 'bmc', 'Frequency distribution of TATA Box and extension sequences on human promoters', 'Shi, Wei|Zhou, Wanlei', 'School of Engineering and Information Technology, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125, Australia. shiwei@deakin.edu.au|School of Engineering and Information Technology, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125, Australia. shiwei@deakin.edu.au', 'Australia|Australia', 15, 'Base Sequence|Binding Sites|Data Interpretation, Statistical|Gene Frequency|Humans|Molecular Sequence Data|Promoter Regions, Genetic|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Statistical Distributions|TATA Box|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-S4-S2', '17217512', 'TATA box is one of the most important transcription factor binding sites. But the exact sequences of TATA box are still not very clear.'),
(91265, 2006, 'bmc', 'Particle simulation approach for subcellular dynamics and interactions of biological molecules', 'Azuma, Ryuzo|Kitagawa, Tetsuji|Kobayashi, Hiroshi|Konagaya, Akihiko', 'RIKEN Genomic Sciences Center, 1-7-22 Suehiro Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. azuma@gsc.riken.jp|RIKEN Genomic Sciences Center, 1-7-22 Suehiro Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. azuma@gsc.riken.jp|RIKEN Genomic Sciences Center, 1-7-22 Suehiro Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. azuma@gsc.riken.jp|RIKEN Genomic Sciences Center, 1-7-22 Suehiro Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. azuma@gsc.riken.jp', 'Japan|Japan|Japan|Japan', 0, 'Biopolymers|Computer Simulation|Diffusion|Models, Biological|Models, Chemical|Nanostructures|Particle Size|Protein Interaction Mapping|Proteins|Subcellular Fractions', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S20', '17217513', 'Spatio-temporal dynamics within cells can now be visualized at appropriate resolution, due to the advances in molecular imaging technologies. Even single-particle tracking (SPT) and single fluorophore video imaging (SFVI) are now being applied to observation of molecular-level dynamics. However, little is known concerning how molecular-level dynamics affect properties at the cellular level.'),
(91266, 2006, 'bmc', 'Combining comparative genomics with de novo motif discovery to identify human transcription factor DNA-binding motifs', 'Mao, Linyong|Zheng, W Jim', 'Department of Biostatistics, Bioinformatics and Epidemiology, and Bioinformatics Core Facility, Hollings Cancer Center, Medical University of South Carolina, 135 Cannon Street, Charleston, SC 29425, USA. maol@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, and Bioinformatics Core Facility, Hollings Cancer Center, Medical University of South Carolina, 135 Cannon Street, Charleston, SC 29425, USA. maol@musc.edu', 'United States|United States', 7, 'Amino Acid Motifs|Base Sequence|Binding Sites|Chromosome Mapping|DNA|Genomics|Humans|Molecular Sequence Data|Multigene Family|Oligonucleotide Array Sequence Analysis|Protein Binding|Regulatory Elements, Transcriptional|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-S4-S21', '17217514', 'As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gene regulations.'),
(91267, 2006, 'bmc', 'Comparison of transcriptional responses in liver tissue and primary hepatocyte cell cultures after exposure to hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine', 'Perkins, Edward J|Bao, Wenjun|Guan, Xin|Ang, Choo-Yaw|Wolfinger, Russell D|Chu, Tzu-Ming|Meyer, Sharon A|Inouye, Laura S', 'US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil|US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS, USA. edward.j.perkins@us.army.mil', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Cells, Cultured|Computer Simulation|Dose-Response Relationship, Drug|Female|Gene Expression|Gene Expression Profiling|Hepatocytes|Liver|Models, Biological|Rats|Rats, Sprague-Dawley|Rodenticides|Transcriptional Activation|Triazines', 'Journal Article', '10.1186/1471-2105-7-S4-S22', '17217515', 'Cell culture systems are useful in studying toxicological effects of chemicals such as Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), however little is known as to how accurately isolated cells reflect responses of intact organs. In this work, we compare transcriptional responses in livers of Sprague-Dawley rats and primary hepatocyte cells after exposure to RDX to determine how faithfully the in vitro model system reflects in vivo responses.'),
(91268, 2006, 'bmc', 'Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method', 'Li, Xiao-Li|Tan, Yin-Chet|Ng, See-Kiong', 'Knowledge Discovery Department, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. xlli@i2r.a-star.edu.sg|Knowledge Discovery Department, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. xlli@i2r.a-star.edu.sg|Knowledge Discovery Department, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. xlli@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore', 21, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Fuzzy Logic|Gene Expression|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S23', '17217516', 'Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. However, there are still gaps toward whole-genome functional annotation of genes using the gene expression data.'),
(91269, 2006, 'bmc', 'A novel approach to phylogenetic tree construction using stochastic optimization and clustering', 'Qin, Ling|Chen, Yixin|Pan, Yi|Chen, Ling', 'Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn', 'China|China|China|China', 0, 'Algorithms|Animals|Ants|Behavior, Animal|Biological Evolution|Biomimetics|Cluster Analysis|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Phylogeny|Social Behavior|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-7-S4-S24', '17217517', 'The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational biology.'),
(91270, 2006, 'bmc', 'SVM Classifier - a comprehensive java interface for support vector machine classification of microarray data', 'Pirooznia, Mehdi|Deng, Youping', 'Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, Mississippi 39406, USA. mehdi.pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, Mississippi 39406, USA. mehdi.pirooznia@usm.edu', 'United States|United States', 29, 'Cluster Analysis|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming Languages|Proteome|Signal Transduction|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S25', '17217518', 'Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction.'),
(91271, 2006, 'bmc', 'AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data', 'Lu, Guoqing|Nguyen, The V|Xia, Yuannan|Fromm, Michael', 'Department of Biology, University of Nebraska, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska, Omaha, NE 68182, USA. glu3@mail.unomaha.edu|Department of Biology, University of Nebraska, Omaha, NE 68182, USA. glu3@mail.unomaha.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Biology|Database Management Systems|Databases, Genetic|Gene Expression|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S26', '17217519', 'DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity, however, qualitative data are also important parameters in detecting differentially expressed genes.'),
(91272, 2006, 'bmc', 'In silico modelling of hormone response elements', 'Stepanova, Maria|Lin, Feng|Lin, Valerie C-L', 'Bioinformatics Research Centre, Nanyang Technological University, 50 Nanyang Drive, Singapore 637553, Singapore. mstepanova@pmail.ntu.edu.sg|Bioinformatics Research Centre, Nanyang Technological University, 50 Nanyang Drive, Singapore 637553, Singapore. mstepanova@pmail.ntu.edu.sg|Bioinformatics Research Centre, Nanyang Technological University, 50 Nanyang Drive, Singapore 637553, Singapore. mstepanova@pmail.ntu.edu.sg', 'Singapore|Singapore|Singapore', 8, 'Binding Sites|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Gonadal Steroid Hormones|Models, Genetic|Pattern Recognition, Automated|Protein Binding|Regulatory Elements, Transcriptional|Response Elements|Sequence Analysis, DNA|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S27', '17217520', 'An important step in understanding the conditions that specify gene expression is the recognition of gene regulatory elements. Due to high diversity of different types of transcription factors and their DNA binding preferences, it is a challenging problem to establish an accurate model for recognition of functional regulatory elements in promoters of eukaryotic genes.'),
(91273, 2006, 'bmc', 'An improved ant colony algorithm with diversified solutions based on the immune strategy', 'Qin, Ling|Pan, Yi|Chen, Ling|Chen, Yixin', 'Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn|Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China. qllynne@nuaa.edu.cn', 'China|China|China|China', 4, 'Algorithms|Animals|Antigen-Antibody Complex|Ants|Behavior, Animal|Biomimetics|Models, Immunological|Social Behavior', 'Journal Article', '10.1186/1471-2105-7-S4-S3', '17217521', 'Ant colony algorithm has emerged recently as a new meta-heuristic method, which is inspired from the behaviours of real ants for solving NP-hard problems. However, the classical ant colony algorithm also has its defects of stagnation and premature. This paper aims at remedying these problems.'),
(91274, 2006, 'bmc', 'A fast parallel algorithm for finding the longest common sequence of multiple biosequences', 'Chen, Yixin|Wan, Andrew|Liu, Wei', 'Department of Computer Science and Engineering, Washington University in St, Louis, St, Louis, MO 63130, USA. chen@cse.wustl.edu|Department of Computer Science and Engineering, Washington University in St, Louis, St, Louis, MO 63130, USA. chen@cse.wustl.edu|Department of Computer Science and Engineering, Washington University in St, Louis, St, Louis, MO 63130, USA. chen@cse.wustl.edu', 'United States|United States|United States', 0, 'Algorithms|Computing Methodologies|Conserved Sequence|Sequence Alignment|Sequence Analysis|Sequence Homology|Time Factors', 'Evaluation Studies', '10.1186/1471-2105-7-S4-S4', '17217522', 'Searching for the longest common sequence (LCS) of multiple biosequences is one of the most fundamental tasks in bioinformatics. In this paper, we present a parallel algorithm named FAST_LCS to speedup the computation for finding LCS.'),
(91275, 2006, 'bmc', 'Estimate haplotype frequencies in pedigrees', 'Zhang, Qiangfeng|Zhao, Yuzhong|Chen, Guoliang|Xu, Yun', 'Department of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230027, China. qfzhang@mail.ustc.edu.cn|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230027, China. qfzhang@mail.ustc.edu.cn|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230027, China. qfzhang@mail.ustc.edu.cn|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230027, China. qfzhang@mail.ustc.edu.cn', 'China|China|China|China', 0, 'Base Sequence|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Gene Frequency|Genetic Variation|Haplotypes|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pedigree|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-S4-S5', '17217523', 'Haplotype analysis has gained increasing attention in the context of association studies of disease genes and drug responsivities over the last years. The potential use of haplotypes has led to the initiation of the HapMap project which is to investigate haplotype patterns in the human genome in different populations. Haplotype inference and frequency estimation are essential components of this endeavour.'),
(91276, 2006, 'bmc', 'Maximum common subgraph: some upper bound and lower bound results', 'Huang, Xiuzhen|Lai, Jing|Jennings, Steven F', 'Department of Computer Science, Arkansas State University, State University, Arkansas 72467, USA. xzhuang@csm.astate.edu|Department of Computer Science, Arkansas State University, State University, Arkansas 72467, USA. xzhuang@csm.astate.edu|Department of Computer Science, Arkansas State University, State University, Arkansas 72467, USA. xzhuang@csm.astate.edu', 'United States|United States|United States', 0, 'Algorithms|Biopolymers|Computer Simulation|Models, Chemical|Models, Molecular|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-S4-S6', '17217524', 'Structure matching plays an important part in understanding the functional role of biological structures. Bioinformatics assists in this effort by reformulating this process into a problem of finding a maximum common subgraph between graphical representations of these structures. Among the many different variants of the maximum common subgraph problem, the maximum common induced subgraph of two graphs is of special interest.'),
(91277, 2006, 'bmc', 'FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis', 'Liang, Lily R|Lu, Shiyong|Wang, Xuena|Lu, Yi|Mandal, Vinay|Patacsil, Dorrelyn|Kumar, Deepak', 'Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu|Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA. lliang@udc.edu', 'United States|United States|United States|United States|United States|United States|United States', 22, 'Algorithms|Biomarkers, Tumor|Computer Simulation|Diagnosis, Computer-Assisted|Fuzzy Logic|Gene Expression Profiling|Humans|Lung Neoplasms|Models, Biological|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-S4-S7', '17217525', 'Microarray techniques have revolutionized genomic research by making it possible to monitor the expression of thousands of genes in parallel. As the amount of microarray data being produced is increasing at an exponential rate, there is a great demand for efficient and effective expression data analysis tools. Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention.'),
(91278, 2006, 'bmc', 'The impact of sample imbalance on identifying differentially expressed genes', 'Yang, Kun|Li, Jianzhong|Gao, Hong', 'Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China. kunyang@hit.edu.cn|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China. kunyang@hit.edu.cn|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China. kunyang@hit.edu.cn', 'China|China|China', 16, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-7-S4-S8', '17217526', 'Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the problem of sample imbalance and there is no study to investigate the impact of sample imbalance on identifying differential expression genes. In addition, it is not clear which method is more suitable for the unbalanced data.'),
(91279, 2006, 'bmc', 'Degenerated primer design to amplify the heavy chain variable region from immunoglobulin cDNA', 'Wang, Ying|Chen, Wei|Li, Xu|Cheng, Bing', 'Center for Laboratory Medicine, First Teaching Hospital of Medical School, Xian Jiaotong University, Xian 710061, China. ywang00@sohu.com|Center for Laboratory Medicine, First Teaching Hospital of Medical School, Xian Jiaotong University, Xian 710061, China. ywang00@sohu.com|Center for Laboratory Medicine, First Teaching Hospital of Medical School, Xian Jiaotong University, Xian 710061, China. ywang00@sohu.com|Center for Laboratory Medicine, First Teaching Hospital of Medical School, Xian Jiaotong University, Xian 710061, China. ywang00@sohu.com', 'China|China|China|China', 0, 'Cell Line|DNA Primers|DNA, Complementary|Gene Rearrangement|Hybridomas|Immunoglobulin Variable Region|Nucleic Acid Amplification Techniques|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-S4-S9', '17217527', 'The amplification of variable regions of immunoglobulins has become a major challenge in the cloning of antibody genes, whether from hybridoma cell lines or splenic B cells. Using conventional protocols, the heavy-chain variable region genes often are not amplified successfully from the hybridoma cell lines.'),
(91280, 2007, 'bmc', 'In silico panning for a non-competitive peptide inhibitor', 'Yagi, Yukiko|Terada, Kotaro|Noma, Takahisa|Ikebukuro, Kazunori|Sode, Koji', 'Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-machi, Koganei, Tokyo, Japan. yagimay@hotmail.com <yagimay@hotmail.com>|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-machi, Koganei, Tokyo, Japan. yagimay@hotmail.com <yagimay@hotmail.com>|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-machi, Koganei, Tokyo, Japan. yagimay@hotmail.com <yagimay@hotmail.com>|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-machi, Koganei, Tokyo, Japan. yagimay@hotmail.com <yagimay@hotmail.com>|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-machi, Koganei, Tokyo, Japan. yagimay@hotmail.com <yagimay@hotmail.com>', 'Japan|Japan|Japan|Japan|Japan', 0, 'Acinetobacter calcoaceticus|Allosteric Site|Binding, Competitive|Combinatorial Chemistry Techniques|Directed Molecular Evolution|Glucose 1-Dehydrogenase|Ligands|Peptide Library|Peptides|Protein Binding|Protein Structure, Secondary|Surface Plasmon Resonance', 'Journal Article', '10.1186/1471-2105-8-11', '17222344', 'Peptide ligands have tremendous therapeutic potential as efficacious drugs. Currently, more than 40 peptides are available in the market for a drug. However, since costly and time-consuming synthesis procedures represent a problem for high-throughput screening, novel procedures to reduce the time and labor involved in screening peptide ligands are required. We propose the novel approach of in silico panning which consists of a two-stage screening, involving affinity selection by docking simulation and evolution of the peptide ligand using genetic algorithms (GAs). In silico panning was successfully applied to the selection of peptide inhibitor for water-soluble quinoprotein glucose dehydrogenase (PQQGDH).'),
(91281, 2007, 'bmc', 'Efficient classification of complete parameter regions based on semidefinite programming', 'Kuepfer, Lars|Sauer, Uwe|Parrilo, Pablo A', 'Institute of Molecular Systems Biology, ETH Zürich, CH-8093 Zürich, Switzerland. lars.kuepfer@imsb.biol.ethz.ch <lars.kuepfer@imsb.biol.ethz.ch>|Institute of Molecular Systems Biology, ETH Zürich, CH-8093 Zürich, Switzerland. lars.kuepfer@imsb.biol.ethz.ch <lars.kuepfer@imsb.biol.ethz.ch>|Institute of Molecular Systems Biology, ETH Zürich, CH-8093 Zürich, Switzerland. lars.kuepfer@imsb.biol.ethz.ch <lars.kuepfer@imsb.biol.ethz.ch>', 'Switzerland|Switzerland|Switzerland', 34, 'Algorithms|Computer Simulation|Kinetics|Metabolic Clearance Rate|Models, Biological|Models, Molecular|Proteome|Signal Transduction|Systems Biology', 'Journal Article', '10.1186/1471-2105-8-12', '17224043', 'Current approaches to parameter estimation are often inappropriate or inconvenient for the modelling of complex biological systems. For systems described by nonlinear equations, the conventional approach is to first numerically integrate the model, and then, in a second a posteriori step, check for consistency with experimental constraints. Hence, only single parameter sets can be considered at a time. Consequently, it is impossible to conclude that the best solution was identified or that no good solution exists, because parameter spaces typically cannot be explored in a reasonable amount of time.'),
(91282, 2007, 'bmc', 'Interpretation of multiple probe sets mapping to the same gene in Affymetrix GeneChips', 'Stalteri, Maria A|Harrison, Andrew P', 'Department of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, UK. mastal@essex.ac.uk <mastal@essex.ac.uk>|Department of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, UK. mastal@essex.ac.uk <mastal@essex.ac.uk>', 'United Kingdom|United Kingdom', 55, 'Animals|Artifacts|DNA Probes|Equipment Failure Analysis|Gene Expression Profiling|Genetic Variation|Mice|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-13', '17224057', 'Affymetrix GeneChip technology enables the parallel observations of tens of thousands of genes. It is important that the probe set annotations are reliable so that biological inferences can be made about genes which undergo differential expression. Probe sets representing the same gene might be expected to show similar fold changes/z-scores, however this is in fact not the case.'),
(91283, 2007, 'bmc', 'Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor stimulation', 'Jelier, Rob|Jenster, Guido|Dorssers, Lambert C J|Wouters, Bas J|Hendriksen, Peter J M|Mons, Barend|Delwel, Ruud|Kors, Jan A', 'Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC--University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Biomarkers, Tumor|Databases, Genetic|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Information Storage and Retrieval|Leukemia, Monocytic, Acute|Male|Natural Language Processing|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Receptors, Androgen|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-14', '17233900', 'High-throughput experiments, such as with DNA microarrays, typically result in hundreds of genes potentially relevant to the process under study, rendering the interpretation of these experiments problematic. Here, we propose and evaluate an approach to find functional associations between large numbers of genes and other biomedical concepts from free-text literature. For each gene, a profile of related concepts is constructed that summarizes the context in which the gene is mentioned in literature. We assign a weight to each concept in the profile based on a likelihood ratio measure. Gene concept profiles can then be clustered to find related genes and other concepts.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91284, 2007, 'bmc', 'AYUMS: an algorithm for completely automatic quantitation based on LC-MS/MS proteome data and its application to the analysis of signal transduction', 'Saito, Ayumu|Nagasaki, Masao|Oyama, Masaaki|Kozuka-Hata, Hiroko|Semba, Kentaro|Sugano, Sumio|Yamamoto, Tadashi|Miyano, Satoru', 'The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp|The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan. s-ayumu@ims.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 18, 'Algorithms|Carcinoma, Squamous Cell|Cell Line, Tumor|Chromatography, Liquid|Computer Simulation|Gene Expression Profiling|Humans|Mass Spectrometry|Models, Biological|Neoplasm Proteins|Peptide Mapping|Proteome|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-8-15', '17233908', 'Comprehensive description of the behavior of cellular components in a quantitative manner is essential for systematic understanding of biological events. Recent LC-MS/MS (tandem mass spectrometry coupled with liquid chromatography) technology, in combination with the SILAC (Stable Isotope Labeling by Amino acids in Cell culture) method, has enabled us to make relative quantitation at the proteome level. The recent report by Blagoev et al. (Nat. Biotechnol., 22, 1139-1145, 2004) indicated that this method was also applicable for the time-course analysis of cellular signaling events. Relative quatitation can easily be performed by calculating the ratio of peak intensities corresponding to differentially labeled peptides in the MS spectrum. As currently available software requires some GUI applications and is time-consuming, it is not suitable for processing large-scale proteome data.'),
(91285, 2007, 'bmc', 'Multivariate analysis and visualization of splicing correlations in single-gene transcriptomes', 'Emerick, Mark C|Parmigiani, Giovanni|Agnew, William S', 'Department of Physiology, Johns Hopkins Medical School, Baltimore, MD 21205 USA. memeri@jhmi.edu|Department of Physiology, Johns Hopkins Medical School, Baltimore, MD 21205 USA. memeri@jhmi.edu|Department of Physiology, Johns Hopkins Medical School, Baltimore, MD 21205 USA. memeri@jhmi.edu', 'United States|United States|United States', 0, 'Alternative Splicing|Gene Library|Genetic Variation|Humans|Models, Genetic|Multivariate Analysis|RNA Splice Sites|RNA Splicing|Spliceosomes|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-8-16', '17233916', 'RNA metabolism, through combinatorial splicing, can generate enormous structural diversity in the proteome. Alternative domains may interact, however, with unpredictable phenotypic consequences, necessitating integrated RNA-level regulation of molecular composition. Splicing correlations within transcripts of single genes provide valuable clues to functional relationships among molecular domains as well as genomic targets for higher-order splicing regulation.'),
(91286, 2007, 'bmc', 'Publishing perishing? Towards tomorrows information architecture', 'Seringhaus, Michael R|Gerstein, Mark B', 'Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520, USA. michael.seringhaus@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520, USA. michael.seringhaus@yale.edu', 'United States|United States', 59, 'Abstracting and Indexing as Topic|Computational Biology|Computing Methodologies|Databases, Factual|Internet|Periodicals as Topic|Publishing|Saccharomyces cerevisiae', 'Editorial', '10.1186/1471-2105-8-17', '17239245', 'Scientific articles are tailored to present information in human-readable aliquots. Although the Internet has revolutionized the way our society thinks about information, the traditional text-based framework of the scientific article remains largely unchanged. This format imposes sharp constraints upon the type and quantity of biological information published today. Academic journals alone cannot capture the findings of modern genome-scale inquiry. Like many other disciplines, molecular biology is a science of facts: information inherently suited to database storage. In the past decade, a proliferation of public and private databases has emerged to house genome sequence, protein structure information, functional genomics data and more, these digital repositories are now a vital component of scientific communication. The next challenge is to integrate this vast and ever-growing body of information with academic journals and other media. To truly integrate scientific information we must modernize academic publishing to exploit the power of the Internet. This means more than online access to articles, hyperlinked references and web-based supplemental data, it means making articles fully computer-readable with intelligent markup and Structured Digital Abstracts.Here, we examine the changing roles of scholarly journals and databases. We present our vision of the optimal information architecture for the biosciences, and close with tangible steps to improve our handling of scientific information today while paving the way for an expansive central index in the future.'),
(91287, 2007, 'bmc', 'PILER-CR: fast and accurate identification of CRISPR repeats', 'Edgar, Robert C', 'bob@drive5.com', '-', 158, 'Algorithms|Archaea|Bacteria|Conserved Sequence|DNA, Archaeal|DNA, Bacterial|Genomics|Information Storage and Retrieval|Repetitive Sequences, Nucleic Acid|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/1471-2105-8-18', '17239253', 'Sequencing of prokaryotic genomes has recently revealed the presence of CRISPR elements: short, highly conserved repeats separated by unique sequences of similar length. The distinctive sequence signature of CRISPR repeats can be found using general-purpose repeat- or pattern-finding software tools. However, the output of such tools is not always ideal for studying these repeats, and significant effort is sometimes needed to build additional tools and perform manual analysis of the output.'),
(91288, 2007, 'bmc', 'Statistical significance of cis-regulatory modules', 'Schones, Dustin E|Smith, Andrew D|Zhang, Michael Q', 'Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu', 'United States|United States|United States', 0, 'Algorithms|Binding Sites|Chromosome Mapping|Cluster Analysis|Computer Simulation|Models, Genetic|Models, Statistical|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Software|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-8-19', '17241466', 'It is becoming increasingly important for researchers to be able to scan through large genomic regions for transcription factor binding sites or clusters of binding sites forming cis-regulatory modules. Correspondingly, there has been a push to develop algorithms for the rapid detection and assessment of cis-regulatory modules. While various algorithms for this purpose have been introduced, most are not well suited for rapid, genome scale scanning.'),
(91289, 2007, 'bmc', 'Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory', 'Sayyed-Ahmad, Abdallah|Tuncay, Kagan|Ortoleva, Peter J', 'Center for Cell and Virus Theory, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA. asayyeda@cems.umn.edu <asayyeda@cems.umn.edu>|Center for Cell and Virus Theory, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA. asayyeda@cems.umn.edu <asayyeda@cems.umn.edu>|Center for Cell and Virus Theory, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA. asayyeda@cems.umn.edu <asayyeda@cems.umn.edu>', 'India|India|India', 22, 'Computational Biology|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation|Information Theory|Kinetics|Models, Genetic|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-20', '17244365', 'Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding.'),
(91290, 2007, 'bmc', 'GraphDNA: a Java program for graphical display of DNA composition analyses', 'Thomas, Jamie M|Horspool, Daniel|Brown, Gordon|Tcherepanov, Vasily|Upton, Chris', 'Department of Microbiology and Biochemistry, University of Victoria, Victoria, BC, V8W 3P6, Canada. jmthomas@uvic.ca <jmthomas@uvic.ca>|Department of Microbiology and Biochemistry, University of Victoria, Victoria, BC, V8W 3P6, Canada. jmthomas@uvic.ca <jmthomas@uvic.ca>|Department of Microbiology and Biochemistry, University of Victoria, Victoria, BC, V8W 3P6, Canada. jmthomas@uvic.ca <jmthomas@uvic.ca>|Department of Microbiology and Biochemistry, University of Victoria, Victoria, BC, V8W 3P6, Canada. jmthomas@uvic.ca <jmthomas@uvic.ca>|Department of Microbiology and Biochemistry, University of Victoria, Victoria, BC, V8W 3P6, Canada. jmthomas@uvic.ca <jmthomas@uvic.ca>', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Graphics|DNA|DNA Mutational Analysis|Molecular Sequence Data|Polymorphism, Single Nucleotide|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-21', '17244370', 'Under conditions of no strand bias the number of Gs is equal to that of Cs for each DNA strand, similarly, the total number of Ts is equal to that of As. However, within each strand there are considerable local deviations from the A = T and G = C equality. These asymmetries in nucleotide composition have been extensively analyzed in prokaryotic and eukaryotic genomes and related to chromosome organization, transcription orientation and other processes in certain organisms. To carry out analysis of intra-strand nucleotide distribution several graphical methods have been developed.'),
(91291, 2007, 'bmc', 'Gene network interconnectedness and the generalized topological overlap measure', 'Yip, Andy M|Horvath, Steve', 'Department of Mathematics, National University of Singapore, 2, Science Drive 2, Singapore 117543, Singapore. matymha@nus.edu.sg <matymha@nus.edu.sg>|Department of Mathematics, National University of Singapore, 2, Science Drive 2, Singapore 117543, Singapore. matymha@nus.edu.sg <matymha@nus.edu.sg>', 'Singapore|Singapore', 307, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Drosophila melanogaster|Fungal Proteins|Gene Regulatory Networks|Models, Genetic|Models, Statistical|Models, Theoretical|Protein Interaction Mapping', 'Journal Article', '10.1186/1471-2105-8-22', '17250769', 'Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the information on the connection (adjacency) between 2 nodes may be noisy or incomplete, it can be desirable to consider alternative measures of pairwise interconnectedness. Here we study a class of measures that are proportional to the number of neighbors that a pair of nodes share in common. For example, the topological overlap measure by Ravasz et al. 1 can be interpreted as a measure of agreement between the m = 1 step neighborhoods of 2 nodes. Several studies have shown that two proteins having a higher topological overlap are more likely to belong to the same functional class than proteins having a lower topological overlap. Here we address the question whether a measure of topological overlap based on higher-order neighborhoods could give rise to a more robust and sensitive measure of interconnectedness.'),
(91292, 2006, 'bmc', 'Trends in life science grid: from computing grid to knowledge grid', 'Konagaya, Akihiko', 'Genomic Sciences Center, RIKEN, Yokohama, Japan. konagaya@gsc.riken.jp', 'Japan', 0, 'Biological Science Disciplines|Computational Biology|Computing Methodologies|Databases as Topic|Electronic Data Processing|Genomics|Knowledge|Publishing|Sequence Alignment|Socialization', 'Journal Article', '10.1186/1471-2105-7-S5-S10', '17254294', 'Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution.'),
(91293, 2006, 'bmc', 'NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition', 'Tsai, Richard Tzong-Han|Sung, Cheng-Lung|Dai, Hong-Jie|Hung, Hsieh-Chuan|Sung, Ting-Yi|Hsu, Wen-Lian', 'Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, Republic of China. thtsai@iis.sinica.edu.tw', 'China|China|China|China|China|China', 78, 'Biomedical Research|Electronic Data Processing|Information Systems|Pattern Recognition, Automated|Software|Terminology as Topic', 'Evaluation Studies', '10.1186/1471-2105-7-S5-S11', '17254295', 'Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., 2 in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target words closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing.'),
(91294, 2006, 'bmc', 'Curation of viral genomes: challenges, applications and the way forward', 'Kulkarni-Kale, Urmila|Bhosle, Shriram G|Manjari, G Sunitha|Joshi, Manali|Bansode, Sandeep|Kolaskar, Ashok S', 'Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in|Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in|Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in|Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in|Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in|Bioinformatics Centre, University of Pune, Pune 411 007 India. urmila@bioinfo.ernet.in', 'India|India|India|India|India|India', 8, 'Amino Acid Sequence|Antigenic Variation|Computer Simulation|Database Management Systems|Databases, Genetic|Databases, Protein|Genetic Variation|Genome, Viral|Models, Molecular|Molecular Sequence Data|Phylogeny|Sequence Homology, Amino Acid|Vaccines', 'Journal Article', '10.1186/1471-2105-7-S5-S12', '17254296', 'Whole genome sequence data is a step towards generating the parts list of life to understand the underlying principles of Biocomplexity. Genome sequencing initiatives of human and model organisms are targeted efforts towards understanding principles of evolution with an application envisaged to improve human health. These efforts culminated in the development of dedicated resources. Whereas a large number of viral genomes have been sequenced by groups or individuals with an interest to study antigenic variation amongst strains and species. These independent efforts enabled viruses to attain the status of best-represented taxa with the highest number of genomes. However, due to lack of concerted efforts, viral genomic sequences merely remained as entries in the public repositories until recently.'),
(91295, 2006, 'bmc', 'Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach', 'Lin, H H|Han, L Y|Zhang, H L|Zheng, C J|Xie, B|Cao, Z W|Chen, Y Z', 'Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543. honghuang@nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Amino Acid Sequence|Animals|Carrier Proteins|Humans|Metals|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Structural Homology, Protein', 'Evaluation Studies', '10.1186/1471-2105-7-S5-S13', '17254297', 'Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal-binding proteins, and evaluated by an independent set of 31,448 metal-binding and 79,051 non-metal-binding proteins. The computed prediction accuracy is 86.3%, 81.6%, 83.5%, 94.0%, 81.2%, 85.4%, 77.6%, 90.4%, 90.9%, 74.9% and 78.1% for calcium-binding, cobalt-binding, copper-binding, iron-binding, magnesium-binding, manganese-binding, nickel-binding, potassium-binding, sodium-binding, zinc-binding, and all metal-binding proteins respectively. The accuracy for the non-member proteins of each class is 88.2%, 99.9%, 98.1%, 91.4%, 87.9%, 94.5%, 99.2%, 99.9%, 99.9%, 98.0%, and 88.0% respectively. Comparable accuracies were obtained by using a different SVM kernel function. Our method predicts 67% of the 87 metal-binding proteins non-homologous to any protein in the Swissprot database and 85.3% of the 333 proteins of known metal-binding domains as metal-binding. These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.'),
(91296, 2006, 'bmc', 'SVM-based prediction of caspase substrate cleavage sites', 'Wee, Lawrence J K|Tan, Tin Wee|Ranganathan, Shoba', 'Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. lawrence@bic.nus.edu.sg|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. lawrence@bic.nus.edu.sg|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. lawrence@bic.nus.edu.sg', 'Singapore|Singapore|Singapore', 50, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Caspases|Computational Biology|Molecular Sequence Data|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-S5-S14', '17254298', 'Caspases belong to a class of cysteine proteases which function as critical effectors in apoptosis and inflammation by cleaving substrates immediately after unique sites. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. Recently, different computational methods have been developed to predict the cleavage sites of caspase substrates with varying degrees of success. As the support vector machines (SVM) algorithm has been shown to be useful in several biological classification problems, we have implemented an SVM-based method to investigate its applicability to this domain.'),
(91297, 2006, 'bmc', 'Splice site identification using probabilistic parameters and SVM classification', 'Baten, A K M A|Chang, B C H|Halgamuge, S K|Li, Jason', 'Dynamic Systems and Control Research Group, DoMME, The University of Melbourne, Victoria 3010, Australia. a.baten@pgrad.unimelb.edu.au|Dynamic Systems and Control Research Group, DoMME, The University of Melbourne, Victoria 3010, Australia. a.baten@pgrad.unimelb.edu.au|Dynamic Systems and Control Research Group, DoMME, The University of Melbourne, Victoria 3010, Australia. a.baten@pgrad.unimelb.edu.au|Dynamic Systems and Control Research Group, DoMME, The University of Melbourne, Victoria 3010, Australia. a.baten@pgrad.unimelb.edu.au', 'Australia|Australia|Australia|Australia', 82, 'Algorithms|Animals|Base Sequence|Eukaryotic Cells|Humans|Markov Chains|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|RNA Splice Sites|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Time Factors', 'Comparative Study', '10.1186/1471-2105-7-S5-S15', '17254299', 'Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and efficient analysis methods. Identifying genes in this newly accumulated data is an important issue in bioinformatics, and it requires the prediction of the complete gene structure. Accurate identification of splice sites in DNA sequences plays one of the central roles of gene structural prediction in eukaryotes. Effective detection of splice sites requires the knowledge of characteristics, dependencies, and relationship of nucleotides in the splice site surrounding region. A higher-order Markov model is generally regarded as a useful technique for modeling higher-order dependencies. However, their implementation requires estimating a large number of parameters, which is computationally expensive.'),
(91298, 2006, 'bmc', 'SPIDer: Saccharomyces protein-protein interaction database', 'Wu, Xiaomei|Zhu, Lei|Guo, Jie|Fu, Cong|Zhou, Hongjun|Dong, Dong|Li, Zhenbo|Zhang, Da-Yong|Lin, Kui', 'MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn|MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China. wuxm@mail.bnu.edu.cn', 'China|China|China|China|China|China|China|China|China', 16, 'Algorithms|Computational Biology|Databases, Genetic|Genome, Fungal|Protein Interaction Mapping|Saccharomyces', 'Journal Article', '10.1186/1471-2105-7-S5-S16', '17254300', 'Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO), we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS) between two GO terms.'),
(91299, 2006, 'bmc', 'Modelling study of dimerization in mammalian defensins', 'Suresh, Anita|Verma, Chandra', 'Biomolecular Modelling and Design Group, Bioinformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671. anita@bii.a-star.edu.sg|Biomolecular Modelling and Design Group, Bioinformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671. anita@bii.a-star.edu.sg', 'Singapore|Singapore', 28, 'Animals|Cations|Cell Membrane|Computer Simulation|Defensins|Dimerization|Humans|Mammals|Models, Molecular|Mutagenesis, Site-Directed|Protein Structure, Quaternary|Sequence Alignment|beta-Defensins', 'Journal Article', '10.1186/1471-2105-7-S5-S17', '17254301', 'Defensins are antimicrobial peptides of innate immunity functioning by non-specific binding to anionic phospholipids in bacterial membranes. Their cationicity, amphipathicity and ability to oligomerize are considered key factors for their action. Based on structural information on human beta-defensin 2, we examine homologous defensins from various mammalian species for conserved functional physico-chemical characteristics.'),
(91300, 2006, 'bmc', 'Fly-DPI: database of protein interactomes for D melanogaster in the approach of systems biology', 'Lin, Chung-Yen|Chen, Shu-Hwa|Cho, Chi-Shiang|Chen, Chia-Ling|Lin, Fan-Kai|Lin, Chieh-Hua|Chen, Pao-Yang|Lo, Chen-Zen|Hsiung, Chao A', 'Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, No, 35 Keyan Rd, Zhunan, Miaoli County 350, Taiwan. cylin@iis.sinica.edu.tw', '-|-|-|-|-|-|-|-|-', 0, 'Animals|Databases, Protein|Drosophila melanogaster|Likelihood Functions|Models, Biological|Protein Interaction Mapping|Systems Biology', 'Journal Article', '10.1186/1471-2105-7-S5-S18', '17254302', 'Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions.'),
(91301, 2006, 'bmc', 'An evaluation of human protein-protein interaction data in the public domain', 'Mathivanan, Suresh|Periaswamy, Balamurugan|Gandhi, T K B|Kandasamy, Kumaran|Suresh, Shubha|Mohmood, Riaz|Ramachandra, Y L|Pandey, Akhilesh', 'Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu|Institute of Bioinformatics, International Technology Park, Bangalore, India. suresh@jhmi.edu', 'India|India|India|India|India|India|India|India', 183, 'Animals|Computer Communication Networks|Genetic Diseases, Inborn|Humans|Information Systems|Literature|Protein Interaction Mapping|Public Sector', 'Comparative Study', '10.1186/1471-2105-7-S5-S19', '17254303', 'Protein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations.'),
(91302, 2006, 'bmc', 'Comparative genomics in cyprinids: common carp ESTs help the annotation of the zebrafish genome', 'Christoffels, Alan|Bartfai, Richard|Srinivasan, Hamsa|Komen, Hans|Orban, Laszlo', 'Computational Biology Group, Temasek Life Sciences Laboratory, Singapore. alan@tll.org.sg|Computational Biology Group, Temasek Life Sciences Laboratory, Singapore. alan@tll.org.sg|Computational Biology Group, Temasek Life Sciences Laboratory, Singapore. alan@tll.org.sg|Computational Biology Group, Temasek Life Sciences Laboratory, Singapore. alan@tll.org.sg|Computational Biology Group, Temasek Life Sciences Laboratory, Singapore. alan@tll.org.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore', 35, 'Algorithms|Animals|Carps|Chromosome Mapping|Cyprinidae|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Library|Genome|Genomics|Male|Sequence Homology, Nucleic Acid|Testis|Untranslated Regions|Zebrafish', 'Comparative Study', '10.1186/1471-2105-7-S5-S2', '17254304', 'Automatic annotation of sequenced eukaryotic genomes integrates a combination of methodologies such as ab-initio methods and alignment of homologous genes and/or proteins. For example, annotation of the zebrafish genome within Ensembl relies heavily on available cDNA and protein sequences from two distantly related fish species and other vertebrates that have diverged several hundred million years ago. The scarcity of genomic information from other cyprinids provides the impetus to leverage EST collections to understand gene structures in this diverse teleost group.'),
(91303, 2006, 'bmc', 'MicroTar: predicting microRNA targets from RNA duplexes', 'Thadani, Rahul|Tammi, Martti T', 'Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543. rahul.thadani@nus.edu.sg|Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543. rahul.thadani@nus.edu.sg', 'Singapore|Singapore', 0, 'Algorithms|Animals|Caenorhabditis elegans|Drosophila melanogaster|Mice|MicroRNAs|Nucleic Acid Conformation|Nucleic Acid Heteroduplexes|RNA, Messenger|Software', 'Journal Article', '10.1186/1471-2105-7-S5-S20', '17254305', 'The accurate prediction of a comprehensive set of messenger RNAs (targets) regulated by animal microRNAs (miRNAs) remains an open problem. In particular, the prediction of targets that do not possess evolutionarily conserved complementarity to their miRNA regulators is not adequately addressed by current tools.'),
(91304, 2006, 'bmc', 'Asymptotic behaviour and optimal word size for exact and approximate word matches between random sequences', 'Forêt, Sylvain|Kantorovitz, Miriam R|Burden, Conrad J', 'Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. sylvain.foret@rsbs.anu.edu.au|Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. sylvain.foret@rsbs.anu.edu.au|Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. sylvain.foret@rsbs.anu.edu.au', 'Australia|Australia|Australia', 0, 'Algorithms|Computational Biology|Mathematical Computing|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology', 'Comparative Study', '10.1186/1471-2105-7-S5-S21', '17254306', 'The number of k-words shared between two sequences is a simple and efficient alignment-free sequence comparison method. This statistic, D2, has been used for the clustering of EST sequences. Sequence comparison based on D2 is extremely fast, its runtime is proportional to the size of the sequences under scrutiny, whereas alignment-based comparisons have a worst-case run time proportional to the square of the size. Recent studies have tackled the rigorous study of the statistical distribution of D2, and asymptotic regimes have been derived. The distribution of approximate k-word matches has also been studied.'),
(91305, 2006, 'bmc', 'Selecting effective siRNA sequences by using radial basis function network and decision tree learning', 'Takasaki, Shigeru|Kawamura, Yoshihiro|Konagaya, Akihiko', 'RIKEN Genomic Sciences Center, Suehiro-cho 1-7-22-E216, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan. takasaki@gsc.riken.jp|RIKEN Genomic Sciences Center, Suehiro-cho 1-7-22-E216, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan. takasaki@gsc.riken.jp|RIKEN Genomic Sciences Center, Suehiro-cho 1-7-22-E216, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan. takasaki@gsc.riken.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Artificial Intelligence|Decision Trees|Neural Networks (Computer)|RNA, Small Interfering|Sequence Analysis, RNA', 'Comparative Study', '10.1186/1471-2105-7-S5-S22', '17254307', 'Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are only a few consistencies among the recently reported design rules/guidelines for selecting siRNA sequences effective for mammalian genes. Another shortcoming of the previously reported methods is that they cannot estimate the probability that a candidate sequence will silence the target gene.'),
(91306, 2006, 'bmc', 'Evaluation and comparison of mammalian subcellular localization prediction methods', 'Sprenger, Josefine|Fink, J Lynn|Teasdale, Rohan D', 'ARC Special Research Centre for Functional and Applied Genomics, Brisbane, QLD 4072, Australia. j.sprenger@imb.uq.edu.au|ARC Special Research Centre for Functional and Applied Genomics, Brisbane, QLD 4072, Australia. j.sprenger@imb.uq.edu.au|ARC Special Research Centre for Functional and Applied Genomics, Brisbane, QLD 4072, Australia. j.sprenger@imb.uq.edu.au', 'Australia|Australia|Australia', 0, 'Animals|Computational Biology|Databases, Factual|Humans|Mammals|Protein Transport|Sensitivity and Specificity|Software|Subcellular Fractions', 'Comparative Study', '10.1186/1471-2105-7-S5-S3', '17254308', 'Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance.'),
(91307, 2006, 'bmc', 'Large-scale analysis of antigenic diversity of T-cell epitopes in dengue virus', 'Khan, Asif M|Heiny, A T|Lee, Kenneth X|Srinivasan, K N|Tan, Tin Wee|August, J Thomas|Brusic, Vladimir', 'The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg|The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 29, 'Amino Acid Sequence|Antigenic Variation|Computational Biology|Databases, Protein|Dengue Virus|Epitopes, T-Lymphocyte|Molecular Sequence Data|Peptide Fragments|Sequence Homology, Amino Acid|Serotyping|Viral Proteins', 'Journal Article', '10.1186/1471-2105-7-S5-S4', '17254309', 'Antigenic diversity in dengue virus strains has been studied, but large-scale and detailed systematic analyses have not been reported. In this study, we report a bioinformatics method for analyzing viral antigenic diversity in the context of T-cell mediated immune responses. We applied this method to study the relationship between short-peptide antigenic diversity and protein sequence diversity of dengue virus. We also studied the effects of sequence determinants on viral antigenic diversity. Short peptides, principally 9-mers were studied because they represent the predominant length of binding cores of T-cell epitopes, which are important for formulation of vaccines.'),
(91308, 2006, 'bmc', 'Projections for fast protein structure retrieval', 'Bhattacharya, Sourangshu|Bhattacharyya, Chiranjib|Chandra, Nagasuma R', 'Dept, of Computer Science and Automation, Indian Institute of Science, Bangalore-560012, India. sourangshu@csa.iisc.ernet.in|Dept, of Computer Science and Automation, Indian Institute of Science, Bangalore-560012, India. sourangshu@csa.iisc.ernet.in|Dept, of Computer Science and Automation, Indian Institute of Science, Bangalore-560012, India. sourangshu@csa.iisc.ernet.in', 'India|India|India', 0, 'Algorithms|Amino Acid Motifs|Databases, Protein|Information Storage and Retrieval|Models, Biological|Models, Molecular|Protein Structure, Tertiary|Structural Homology, Protein|Time Factors', 'Comparative Study', '10.1186/1471-2105-7-S5-S5', '17254310', 'In recent times, there has been an exponential rise in the number of protein structures in databases e.g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly important research issue. This paper reports an algorithm, motivated from spectral graph matching techniques, for retrieving protein structures similar to a query structure from a large protein structure database. Each protein structure is specified by the 3D coordinates of residues of the protein. The algorithm is based on a novel characterization of the residues, called projections, leading to a similarity measure between the residues of the two proteins. This measure is exploited to efficiently compute the optimal equivalences.'),
(91309, 2006, 'bmc', 'Improving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker index', 'Sikder, Abdur R|Zomaya, Albert Y', 'Advanced Networks Research Group, School of Information Technologies, J12, University of Sydney, NSW 2006, Australia. sikder@it.uysd.edu.au|Advanced Networks Research Group, School of Information Technologies, J12, University of Sydney, NSW 2006, Australia. sikder@it.uysd.edu.au', 'Australia|Australia', 0, 'Amino Acid Motifs|Amino Acid Sequence|Databases, Protein|Molecular Sequence Data|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein', 'Comparative Study', '10.1186/1471-2105-7-S5-S6', '17254311', 'Knowledge of protein domain boundaries is critical for the characterisation and understanding of protein function. The ability to identify domains without the knowledge of the structure--by using sequence information only--is an essential step in many types of protein analyses. In this present study, we demonstrate that the performance of DomainDiscovery is improved significantly by including the inter-domain linker index value for domain identification from sequence-based information. Improved DomainDiscovery uses a Support Vector Machine (SVM) approach and a unique training dataset built on the principle of consensus among experts in defining domains in protein structure. The SVM was trained using a PSSM (Position Specific Scoring Matrix), secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence.'),
(91310, 2006, 'bmc', 'Prediction of desmoglein-3 peptides reveals multiple shared T-cell epitopes in HLA DR4- and DR6-associated pemphigus vulgaris', 'Tong, Joo Chuan|Tan, Tin Wee|Sinha, Animesh A|Ranganathan, Shoba', 'Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore. jctong@i2r.a-star.edu.sg|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore. jctong@i2r.a-star.edu.sg|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore. jctong@i2r.a-star.edu.sg|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore. jctong@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 0, 'Amino Acid Sequence|Computational Biology|Cross Reactions|Desmoglein 3|Disease Progression|Epitopes, T-Lymphocyte|HLA-DQ Antigens|HLA-DQ beta-Chains|HLA-DR Antigens|HLA-DR4 Antigen|HLA-DR6 Antigen|HLA-DRB1 Chains|Humans|Models, Statistical|Molecular Sequence Data|Pemphigus|Peptide Fragments', 'Evaluation Studies', '10.1186/1471-2105-7-S5-S7', '17254312', 'Pemphigus vulgaris (PV) is a severe autoimmune blistering skin disorder that is strongly associated with major histocompatibility complex class II alleles DRB1*0402 and DQB1*0503. The target antigen of PV, desmoglein 3 (Dsg3), is crucial for initiating T-cell response in early disease. Although a number of T-cell specificities within Dsg3 have been reported, the number is limited and the role of T-cells in the pathogenesis of PV remains poorly understood. We report here a structure-based model for the prediction of peptide binding to DRB1*0402 and DQB1*0503. The scoring functions were rigorously trained, tested and validated using experimentally verified peptide sequences.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91311, 2006, 'bmc', 'Computational promoter analysis of mouse, rat and human antimicrobial peptide-coding genes', 'Brahmachary, Manisha|Schönbach, Christian|Yang, Liang|Huang, Enli|Tan, Sin Lam|Chowdhary, Rajesh|Krishnan, S P T|Lin, Chin-Yo|Hume, David A|Kai, Chikatoshi|Kawai, Jun|Carninci, Piero|Hayashizaki, Yoshihide|Bajic, Vladimir B', 'Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg|Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore. manisha@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|', 0, 'Animals|Antimicrobial Cationic Peptides|Binding Sites|Carrier Proteins|Computational Biology|Enkephalins|Humans|Mice|Multigene Family|Promoter Regions, Genetic|Protein Precursors|Rats|Sequence Analysis, DNA|Transcription Factors|alpha-Defensins', 'Journal Article', '10.1186/1471-2105-7-S5-S8', '17254313', 'Mammalian antimicrobial peptides (AMPs) are effectors of the innate immune response. A multitude of signals coming from pathways of mammalian pathogen/pattern recognition receptors and other proteins affect the expression of AMP-coding genes (AMPcgs). For many AMPcgs the promoter elements and transcription factors that control their tissue cell-specific expression have yet to be fully identified and characterized.'),
(91312, 2006, 'bmc', 'MycoperonDB: a database of computationally identified operons and transcriptional units in Mycobacteria', 'Ranjan, Sarita|Gundu, Ranjit Kumar|Ranjan, Akash', 'Computational & Functional Genomics Group, Sun Centre of Excellence in Medical Bioinformatics, EMBnet India Node, Hyderabad 500076, India. sarita@cdfd.org.in|Computational & Functional Genomics Group, Sun Centre of Excellence in Medical Bioinformatics, EMBnet India Node, Hyderabad 500076, India. sarita@cdfd.org.in|Computational & Functional Genomics Group, Sun Centre of Excellence in Medical Bioinformatics, EMBnet India Node, Hyderabad 500076, India. sarita@cdfd.org.in', 'India|India|India', 14, 'Cluster Analysis|Conserved Sequence|DNA, Intergenic|Databases, Genetic|Information Storage and Retrieval|Mycobacterium|Open Reading Frames|Operon|Terminator Regions, Genetic|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-S5-S9', '17254314', 'A key post genomics challenge is to identify how genes in an organism come together and perform physiological functions. An important first step in this direction is to identify transcriptional units, operons and regulons in a genome. Here we implement and report a strategy to computationally identify transcriptional units and operons of mycobacteria and construct a database-MycoperonDB.'),
(91313, 2007, 'bmc', 'Motif kernel generated by genetic programming improves remote homology and fold detection', 'Håndstad, Tony|Hestnes, Arne J H|Saetrom, Pål', 'Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052, Trondheim, Norway. tony.handstad@gmail.com|Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052, Trondheim, Norway. tony.handstad@gmail.com|Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052, Trondheim, Norway. tony.handstad@gmail.com', 'Norway|Norway|Norway', 0, 'Algorithms|Amino Acid Motifs|Pattern Recognition, Automated|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1186/1471-2105-8-23', '17254344', 'Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and unrelated sequences and these studies have introduced several types of kernels. One successful approach is to base a kernel on shared occurrences of discrete sequence motifs. Still, many protein sequences fail to be classified correctly for a lack of a suitable set of motifs for these sequences.'),
(91314, 2007, 'bmc', 'Benchmarking natural-language parsers for biological applications using dependency graphs', 'Clegg, Andrew B|Shepherd, Adrian J', 'School of Crystallography, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK. a.clegg@mail.cryst.bbk.ac.uk|School of Crystallography, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK. a.clegg@mail.cryst.bbk.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Benchmarking|Computational Biology|Database Management Systems|Humans|Information Storage and Retrieval|Language|Models, Statistical|Natural Language Processing|Programming Languages|Reproducibility of Results|Software', 'Journal Article', '10.1186/1471-2105-8-24', '17254351', 'Interest is growing in the application of syntactic parsers to natural language processing problems in biology, but assessing their performance is difficult because differences in linguistic convention can falsely appear to be errors. We present a method for evaluating their accuracy using an intermediate representation based on dependency graphs, in which the semantic relationships important in most information extraction tasks are closer to the surface. We also demonstrate how this method can be easily tailored to various application-driven criteria.'),
(91315, 2007, 'bmc', 'Bias in random forest variable importance measures: illustrations, sources and a solution', 'Strobl, Carolin|Boulesteix, Anne-Laure|Zeileis, Achim|Hothorn, Torsten', 'Institut für Statistik, Ludwig-Maximilians-Universität München, Ludwigstr, 33, 80539 München, Germany. carolin.strobl@stat.uni-muenchen.de|Institut für Statistik, Ludwig-Maximilians-Universität München, Ludwigstr, 33, 80539 München, Germany. carolin.strobl@stat.uni-muenchen.de|Institut für Statistik, Ludwig-Maximilians-Universität München, Ludwigstr, 33, 80539 München, Germany. carolin.strobl@stat.uni-muenchen.de|Institut für Statistik, Ludwig-Maximilians-Universität München, Ludwigstr, 33, 80539 München, Germany. carolin.strobl@stat.uni-muenchen.de', 'Germany|Germany|Germany|Germany', 1196, 'Algorithms|Bias|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Genomics|Models, Biological|Models, Statistical|Population Dynamics', 'Journal Article', '10.1186/1471-2105-8-25', '17254353', 'Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories.'),
(91316, 2007, 'bmc', 'Missing channels in two-colour microarray experiments: combining single-channel and two-channel data', 'Lynch, Andy G|Neal, David E|Kelly, John D|Burtt, Glyn J|Thorne, Natalie P', 'Department of Oncology, University of Cambridge, Cambridge, UK. dr@andrewlynch.co.uk|Department of Oncology, University of Cambridge, Cambridge, UK. dr@andrewlynch.co.uk|Department of Oncology, University of Cambridge, Cambridge, UK. dr@andrewlynch.co.uk|Department of Oncology, University of Cambridge, Cambridge, UK. dr@andrewlynch.co.uk|Department of Oncology, University of Cambridge, Cambridge, UK. dr@andrewlynch.co.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Artifacts|Biomarkers, Tumor|Gene Expression Profiling|Humans|Microscopy, Fluorescence, Multiphoton|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-26', '17254358', 'There are mechanisms, notably ozone degradation, that can damage a single channel of two-channel microarray experiments. Resulting analyses therefore often choose between the unacceptable inclusion of poor quality data or the unpalatable exclusion of some (possibly a lot of) good quality data along with the bad. Two such approaches would be a single channel analysis using some of the data from all of the arrays, and an analysis of all of the data, but only from unaffected arrays. In this paper we examine a combined approach to the analysis of such affected experiments that uses all of the unaffected data.'),
(91317, 2007, 'bmc', 'Scoring functions and enrichment: a case study on Hsp90', 'Konstantinou-Kirtay, Chrysi|Mitchell, John B O|Lumley, James A', 'Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, UK. ck302@cam.ac.uk <ck302@cam.ac.uk>|Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, UK. ck302@cam.ac.uk <ck302@cam.ac.uk>|Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, UK. ck302@cam.ac.uk <ck302@cam.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom', 11, 'Algorithms|Binding Sites|Computer Simulation|Drug Design|HSP90 Heat-Shock Proteins|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-27', '17257425', 'The need for fast and accurate scoring functions has been driven by the increased use of in silico virtual screening twinned with high-throughput screening as a method to rapidly identify potential candidates in the early stages of drug development. We examine the ability of some the most common scoring functions (GOLD, ChemScore, DOCK, PMF, BLEEP and Consensus) to discriminate correctly and efficiently between active and non-active compounds among a library of approximately 3,600 diverse decoy compounds in a virtual screening experiment against heat shock protein 90 (Hsp90).'),
(91318, 2007, 'bmc', 'Detecting differential expression in microarray data: comparison of optimal procedures', 'Perelman, Elena|Ploner, Alexander|Calza, Stefano|Pawitan, Yudi', 'Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden. lenaperelman@gmail.com <lenaperelman@gmail.com>|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden. lenaperelman@gmail.com <lenaperelman@gmail.com>|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden. lenaperelman@gmail.com <lenaperelman@gmail.com>|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden. lenaperelman@gmail.com <lenaperelman@gmail.com>', 'Sweden|Sweden|Sweden|Sweden', 12, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Software', 'Journal Article', '10.1186/1471-2105-8-28', '17257426', 'Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, the false discovery rate (FDR) is the key tool for assessing the significance of these test statistics. Two recent papers have generalized two aspects: Storey et al. (2005) have introduced a likelihood ratio test statistic for two-sample situations that has desirable theoretical properties (optimal discovery procedure, ODP), but uses standard FDR assessment, Ploner et al. (2006) have introduced a multivariate local FDR that allows incorporation of standard error information, but uses the standard t-statistic (fdr2d). The relationship and relative performance of these methods in two-sample comparisons is currently unknown.'),
(91319, 2007, 'bmc', 'Measuring similarities between gene expression profiles through new data transformations', 'Kim, Kyungpil|Zhang, Shibo|Jiang, Keni|Cai, Li|Lee, In-Beum|Feldman, Lewis J|Huang, Haiyan', 'Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>|Department of Statistics, University of California, Berkeley, USA. kpkim@stat.berkeley.edu <kpkim@stat.berkeley.edu>', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Multigene Family|Pattern Recognition, Automated|Proteome|Signal Transduction|Software', 'Evaluation Studies', '10.1186/1471-2105-8-29', '17257435', 'Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is critical to the analysis. In our study, we developed a new measure for clustering the genes when the key factor is the shape of the profile, and when the expression magnitude should also be accounted for in determining the gene relationship. This is achieved by modeling the shape and magnitude parameters separately in a gene expression profile, and then using the estimated shape and magnitude parameters to define a measure in a new feature space.'),
(91320, 2007, 'bmc', 'Hybrid elementary flux analysis/nonparametric modeling: application for bioprocess control', 'Teixeira, Ana P|Alves, Carlos|Alves, Paula M|Carrondo, Manuel J T|Oliveira, Rui', 'IBET/ITQB, Apartado 12, P-2781-901 Oeiras, Portugal. ana.teixeira@dq.fct.unl.pt <ana.teixeira@dq.fct.unl.pt>|IBET/ITQB, Apartado 12, P-2781-901 Oeiras, Portugal. ana.teixeira@dq.fct.unl.pt <ana.teixeira@dq.fct.unl.pt>|IBET/ITQB, Apartado 12, P-2781-901 Oeiras, Portugal. ana.teixeira@dq.fct.unl.pt <ana.teixeira@dq.fct.unl.pt>|IBET/ITQB, Apartado 12, P-2781-901 Oeiras, Portugal. ana.teixeira@dq.fct.unl.pt <ana.teixeira@dq.fct.unl.pt>|IBET/ITQB, Apartado 12, P-2781-901 Oeiras, Portugal. ana.teixeira@dq.fct.unl.pt <ana.teixeira@dq.fct.unl.pt>', 'Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|Animals|CHO Cells|Computer Simulation|Cricetinae|Cricetulus|Metabolic Clearance Rate|Models, Biological|Protein Engineering|Proteome|Recombinant Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-30', '17261182', 'The progress in the -omic sciences has allowed a deeper knowledge on many biological systems with industrial interest. This knowledge is still rarely used for advanced bioprocess monitoring and control at the bioreactor level. In this work, a bioprocess control method is presented, which is designed on the basis of the metabolic network of the organism under consideration. The bioprocess dynamics are formulated using hybrid rigorous/data driven systems and its inherent structure is defined by the metabolism elementary modes.'),
(91321, 2007, 'bmc', 'Conceptual-level workflow modeling of scientific experiments using NMR as a case study', 'Verdi, Kacy K|Ellis, Heidi Jc|Gryk, Michael R', 'Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. kverdi@alum.rpi.edu <kverdi@alum.rpi.edu>|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. kverdi@alum.rpi.edu <kverdi@alum.rpi.edu>|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. kverdi@alum.rpi.edu <kverdi@alum.rpi.edu>', 'United States|United States|United States', 11, 'Decision Support Techniques|Documentation|Laboratories|Magnetic Resonance Spectroscopy|Models, Organizational|Research|Science|Software|Workplace', 'Journal Article', '10.1186/1471-2105-8-31', '17263870', 'Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration.'),
(91322, 2007, 'bmc', 'Context based mixture model for cell phase identification in automated fluorescence microscopy', 'Wang, Meng|Zhou, Xiaobo|King, Randy W|Wong, Stephen T C', 'Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA. bioinformaticswang@gmail.com <bioinformaticswang@gmail.com>|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA. bioinformaticswang@gmail.com <bioinformaticswang@gmail.com>|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA. bioinformaticswang@gmail.com <bioinformaticswang@gmail.com>|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA. bioinformaticswang@gmail.com <bioinformaticswang@gmail.com>', 'United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Cell Cycle|Cell Nucleus|Computer Simulation|HeLa Cells|Humans|Image Enhancement|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Models, Biological|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-8-32', '17263881', 'Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task.'),
(91323, 2007, 'bmc', 'Considerations in the identification of functional RNA structural elements in genomic alignments', 'Babak, Tomas|Blencowe, Benjamin J|Hughes, Timothy R', 'Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, 160 College St, Toronto, ON M5S 3E1 Canada. tomas.babak@utoronto.ca <tomas.babak@utoronto.ca>|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, 160 College St, Toronto, ON M5S 3E1 Canada. tomas.babak@utoronto.ca <tomas.babak@utoronto.ca>|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, 160 College St, Toronto, ON M5S 3E1 Canada. tomas.babak@utoronto.ca <tomas.babak@utoronto.ca>', 'Canada|Canada|Canada', 47, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1186/1471-2105-8-33', '17263882', 'Accurate identification of novel, functional noncoding (nc) RNA features in genome sequence has proven more difficult than for exons. Current algorithms identify and score potential RNA secondary structures on the basis of thermodynamic stability, conservation, and/or covariance in sequence alignments. Neither the algorithms nor the information gained from the individual inputs have been independently assessed. Furthermore, due to issues in modelling background signal, it has been difficult to gauge the precision of these algorithms on a genomic scale, in which even a seemingly small false-positive rate can result in a vast excess of false discoveries.'),
(91324, 2007, 'bmc', 'Computational RNA secondary structure design: empirical complexity and improved methods', 'Aguirre-Hernández, Rosalía|Hoos, Holger H|Condon, Anne', 'Institute of Applied Mathematics, University of British Columbia, Vancouver, BC, Canada. rosalia@cs.ubc.ca <rosalia@cs.ubc.ca>|Institute of Applied Mathematics, University of British Columbia, Vancouver, BC, Canada. rosalia@cs.ubc.ca <rosalia@cs.ubc.ca>|Institute of Applied Mathematics, University of British Columbia, Vancouver, BC, Canada. rosalia@cs.ubc.ca <rosalia@cs.ubc.ca>', 'Canada|Canada|Canada', 0, 'Algorithms|Base Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA', 'Comparative Study', '10.1186/1471-2105-8-34', '17266771', 'We investigate the empirical complexity of the RNA secondary structure design problem, that is, the scaling of the typical difficulty of the design task for various classes of RNA structures as the size of the target structure is increased. The purpose of this work is to understand better the factors that make RNA structures hard to design for existing, high-performance algorithms. Such understanding provides the basis for improving the performance of one of the best algorithms for this problem, RNA-SSD, and for characterising its limitations.'),
(91325, 2007, 'bmc', 'Classification of microarray data using gene networks', 'Rapaport, Franck|Zinovyev, Andrei|Dutreix, Marie|Barillot, Emmanuel|Vert, Jean-Philippe', 'lnstitut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. franck.rapaport@curie.fr|lnstitut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. franck.rapaport@curie.fr|lnstitut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. franck.rapaport@curie.fr|lnstitut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. franck.rapaport@curie.fr|lnstitut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. franck.rapaport@curie.fr', 'France|France|France|France|France', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Proteome|Signal Transduction', 'Evaluation Studies', '10.1186/1471-2105-8-35', '17270037', 'Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation.'),
(91326, 2007, 'bmc', 'GEVALT: an integrated software tool for genotype analysis', 'Davidovich, Ofir|Kimmel, Gad|Shamir, Ron', 'School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. offirdav@post.tau.ac.il|School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. offirdav@post.tau.ac.il|School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. offirdav@post.tau.ac.il', 'Israel|Israel|Israel', 34, 'Algorithms|Biological Evolution|Chromosome Mapping|DNA Mutational Analysis|Genotype|Pedigree|Polymorphism, Single Nucleotide|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-36', '17270038', 'Genotype information generated by individual and international efforts carries the promise of revolutionizing disease studies and the association of phenotypes with alleles and haplotypes. Given the enormous amounts of public genotype data, tools for analyzing, interpreting and visualizing these data sets are of critical importance to researchers. In past works we have developed algorithms for genotypes phasing and tag SNP selection, which were shown to be quick and accurate. Both algorithms were available until now only as batch executables.'),
(91327, 2007, 'bmc', 'Boolean networks using the chi-square test for inferring large-scale gene regulatory networks', 'Kim, Haseong|Lee, Jae K|Park, Taesung', 'Interdisciplinary Program in Bioinformatics, Seoul National University, South Korea. khs@bibs.snu.ac.kr <khs@bibs.snu.ac.kr>|Interdisciplinary Program in Bioinformatics, Seoul National University, South Korea. khs@bibs.snu.ac.kr <khs@bibs.snu.ac.kr>|Interdisciplinary Program in Bioinformatics, Seoul National University, South Korea. khs@bibs.snu.ac.kr <khs@bibs.snu.ac.kr>', '-|-|-', 0, 'Algorithms|Artificial Intelligence|Chi-Square Distribution|Cluster Analysis|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-37', '17270045', 'Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that its computation time is very high or often impractical to construct large-scale gene networks. We propose a variable selection method that are not only reduces BN computation times significantly but also obtains optimal network constructions by using chi-square statistics for testing the independence in contingency tables.'),
(91328, 2007, 'bmc', 'Heritable clustering and pathway discovery in breast cancer integrating epigenetic and phenotypic data', 'Wang, Zailong|Yan, Pearlly|Potter, Dustin|Eng, Charis|Huang, Tim H-M|Lin, Shili', 'Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>|Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>|Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>|Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>|Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>|Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA. zailong.wang@yahoo.com <zailong.wang@yahoo.com>', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Chromosome Mapping|Cluster Analysis|DNA Methylation|DNA, Neoplasm|Epigenesis, Genetic|Evolution, Molecular|Female|Gene Expression Profiling|Humans|Neoplasm Proteins|Phenotype|Signal Transduction|Systems Integration', 'Journal Article', '10.1186/1471-2105-8-38', '17270052', 'In order to recapitulate tumor progression pathways using epigenetic data, we developed novel clustering and pathway reconstruction algorithms, collectively referred to as heritable clustering. This approach generates a progression model of altered DNA methylation from tumor tissues diagnosed at different developmental stages. The samples act as surrogates for natural progression in breast cancer and allow the algorithm to uncover distinct epigenotypes that describe the molecular events underlying this process. Furthermore, our likelihood-based clustering algorithm has great flexibility, allowing for incomplete epigenotype or clinical phenotype data and also permitting dependencies among variables.'),
(91329, 2007, 'bmc', 'Predicting zinc binding at the proteome level', 'Passerini, Andrea|Andreini, Claudia|Menchetti, Sauro|Rosato, Antonio|Frasconi, Paolo', 'Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Italy. passerini@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Italy. passerini@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Italy. passerini@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Italy. passerini@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Italy. passerini@dsi.unifi.it', 'Italy|Italy|Italy|Italy|Italy', 74, 'Algorithms|Amino Acid Sequence|Binding Sites|Metalloproteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteome|Sequence Alignment|Sequence Analysis, Protein|Zinc', 'Journal Article', '10.1186/1471-2105-8-39', '17280606', 'Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for structural purposes. Metal-binding properties remain difficult to predict as well as to investigate experimentally at the whole-proteome level. Consequently, the current knowledge about metalloproteins is only partial.'),
(91330, 2007, 'bmc', 'NeuroTerrain--a client-server system for browsing 3D biomedical image data sets', 'Gustafson, Carl|Bug, William J|Nissanov, Jonathan', 'Laboratory for Bioimaging and Anatomical Informatics, Department of Neurobiology and Anatomy, Drexel University College of Medicine, 2900 Queen Lane, Philadelphia, PA 19129, USA. cgg25@drexel.edu <cgg25@drexel.edu>|Laboratory for Bioimaging and Anatomical Informatics, Department of Neurobiology and Anatomy, Drexel University College of Medicine, 2900 Queen Lane, Philadelphia, PA 19129, USA. cgg25@drexel.edu <cgg25@drexel.edu>|Laboratory for Bioimaging and Anatomical Informatics, Department of Neurobiology and Anatomy, Drexel University College of Medicine, 2900 Queen Lane, Philadelphia, PA 19129, USA. cgg25@drexel.edu <cgg25@drexel.edu>', 'United States|United States|United States', 0, 'Algorithms|Biomedical Engineering|Computer Graphics|Database Management Systems|Databases, Factual|Diagnostic Imaging|Image Enhancement|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Internet|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-40', '17280615', 'Three dimensional biomedical image sets are becoming ubiquitous, along with the canonical atlases providing the necessary spatial context for analysis. To make full use of these 3D image sets, one must be able to present views for 2D display, either surface renderings or 2D cross-sections through the data. Typical display software is limited to presentations along one of the three orthogonal anatomical axes (coronal, horizontal, or sagittal). However, data sets precisely oriented along the major axes are rare. To make fullest use of these datasets, one must reasonably match the atlas orientation, this involves resampling the atlas in planes matched to the data set. Traditionally, this requires the atlas and browser reside on the users desktop, unfortunately, in addition to being monolithic programs, these tools often require substantial local resources. In this article, we describe a network-capable, client-server framework to slice and visualize 3D atlases at off-axis angles, along with an open client architecture and development kit to support integration into complex data analysis environments.'),
(91331, 2007, 'bmc', 'FUNC: a package for detecting significant associations between gene sets and ontological annotations', 'Prüfer, Kay|Muetzel, Bjoern|Do, Hong-Hai|Weiss, Gunter|Khaitovich, Philipp|Rahm, Erhard|Pääbo, Svante|Lachmann, Michael|Enard, Wolfgang', 'Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de|Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Data Interpretation, Statistical|Databases, Genetic|Evolution, Molecular|Gene Expression Profiling|Genome|Humans|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-41', '17284313', 'Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Information about these genes is increasingly being captured and organized in ontologies, such as the Gene Ontology. Relationships between the gene sets identified by experimental methods and biological knowledge can be made explicit and used in the interpretation of results. However, it is often difficult to assess the statistical significance of such analyses since many inter-dependent categories are tested simultaneously.'),
(91332, 2007, 'bmc', 'PlnTFDB: an integrative plant transcription factor database', 'Riaño-Pachón, Diego Mauricio|Ruzicic, Slobodan|Dreyer, Ingo|Mueller-Roeber, Bernd', 'Department of Molecular Biology, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 25 Haus 20, D-14476, Golm, Germany. diriano@uni-potsdam.de|Department of Molecular Biology, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 25 Haus 20, D-14476, Golm, Germany. diriano@uni-potsdam.de|Department of Molecular Biology, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 25 Haus 20, D-14476, Golm, Germany. diriano@uni-potsdam.de|Department of Molecular Biology, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 25 Haus 20, D-14476, Golm, Germany. diriano@uni-potsdam.de', 'Germany|Germany|Germany|Germany', 0, 'Databases, Protein|Gene Expression Regulation, Plant|Gene Regulatory Networks|Genome, Plant|Plants|Promoter Regions, Genetic|Sequence Alignment|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-42', '17286856', 'Transcription factors (TFs) are key regulatory proteins that enhance or repress the transcriptional rate of their target genes by binding to specific promoter regions (i.e. cis-acting elements) upon activation or de-activation of upstream signaling cascades. TFs thus constitute master control elements of dynamic transcriptional networks. TFs have fundamental roles in almost all biological processes (development, growth and response to environmental factors) and it is assumed that they play immensely important functions in the evolution of species. In plants, TFs have been employed to manipulate various types of metabolic, developmental and stress response pathways. Cross-species comparison and identification of regulatory modules and hence TFs is thought to become increasingly important for the rational design of new plant biomass. Up to now, however, no computational repository is available that provides access to the largely complete sets of transcription factors of sequenced plant genomes.'),
(91333, 2007, 'bmc', 'Predictive modeling of plant messenger RNA polyadenylation sites', 'Ji, Guoli|Zheng, Jianti|Shen, Yingjia|Wu, Xiaohui|Jiang, Ronghan|Lin, Yun|Loke, Johnny C|Davis, Kimberly M|Reese, Greg J|Li, Qingshun Quinn', 'Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn|Department of Automation, Xiamen University, Xiamen, Fujian, 361005, PR China. glji@xmu.edu.cn', 'China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Arabidopsis|Computer Simulation|RNA Processing, Post-Transcriptional|RNA, Messenger|RNA, Plant|Sensitivity and Specificity|mRNA Cleavage and Polyadenylation Factors', 'Evaluation Studies', '10.1186/1471-2105-8-43', '17286857', 'One of the essential processing events during pre-mRNA maturation is the post-transcriptional addition of a polyadenine [poly(A)] tail. The 3-end poly(A) track protects mRNA from unregulated degradation, and indicates the integrity of mRNA through recognition by mRNA export and translation machinery. The position of a poly(A) site is predetermined by signals in the pre-mRNA sequence that are recognized by a complex of polyadenylation factors. These signals are generally tri-part sequence patterns around the cleavage site that serves as the future poly(A) site. In plants, there is little sequence conservation among these signal elements, which makes it difficult to develop an accurate algorithm to predict the poly(A) site of a given gene. We attempted to solve this problem.'),
(91334, 2007, 'bmc', 'Ranked Adjusted Rand: integrating distance and partition information in a measure of clustering agreement', 'Pinto, Francisco R|Carriço, João A|Ramirez, Mário|Almeida, Jonas S', 'Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Av, Professor Egas Moniz, 1649-028 Lisboa, Portugal. fpinto@fm.ul.pt|Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Av, Professor Egas Moniz, 1649-028 Lisboa, Portugal. fpinto@fm.ul.pt|Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Av, Professor Egas Moniz, 1649-028 Lisboa, Portugal. fpinto@fm.ul.pt|Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Av, Professor Egas Moniz, 1649-028 Lisboa, Portugal. fpinto@fm.ul.pt', 'Portugal|Portugal|Portugal|Portugal', 12, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Databases, Factual|Information Storage and Retrieval|Models, Biological', 'Journal Article', '10.1186/1471-2105-8-44', '17286861', 'Biological information is commonly used to cluster or classify entities of interest such as genes, conditions, species or samples. However, different sources of data can be used to classify the same set of entities and methods allowing the comparison of the performance of two data sources or the determination of how well a given classification agrees with another are frequently needed, especially in the absence of a universally accepted gold standard classification.'),
(91335, 2007, 'bmc', 'Identifying allosteric fluctuation transitions between different protein conformational states as applied to Cyclin Dependent Kinase 2', 'Gu, Jenny|Bourne, Philip E', 'Department of Pharmacology and Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA. jgu@sdsc.edu|Department of Pharmacology and Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA. jgu@sdsc.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Cyclin-Dependent Kinase 2|Isomerism|Kinetics|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Sequence Analysis, Protein|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1186/1471-2105-8-45', '17286863', 'The mechanisms underlying protein function and associated conformational change are dominated by a series of local entropy fluctuations affecting the global structure yet are mediated by only a few key residues. Transitional Dynamic Analysis (TDA) is a new method to detect these changes in local protein flexibility between different conformations arising from, for example, ligand binding. Additionally, Positional Impact Vertex for Entropy Transfer (PIVET) uses TDA to identify important residue contact changes that have a large impact on global fluctuation. We demonstrate the utility of these methods for Cyclin-dependent kinase 2 (CDK2), a system with crystal structures of this protein in multiple functionally relevant conformations and experimental data revealing the importance of local fluctuation changes for protein function.'),
(91336, 2007, 'bmc', 'WeederH: an algorithm for finding conserved regulatory motifs and regions in homologous sequences', 'Pavesi, Giulio|Zambelli, Federico|Pesole, Graziano', 'Dipartimento di Scienze Biomolecolari e Biotecnologie, University of Milan, Milan, Italy. giulio.pavesi@unimi.it|Dipartimento di Scienze Biomolecolari e Biotecnologie, University of Milan, Milan, Italy. giulio.pavesi@unimi.it|Dipartimento di Scienze Biomolecolari e Biotecnologie, University of Milan, Milan, Italy. giulio.pavesi@unimi.it', 'Italy|Italy|Italy', 30, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Conserved Sequence|Molecular Sequence Data|Protein Binding|Regulatory Sequences, Nucleic Acid|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-46', '17286865', 'This work addresses the problem of detecting conserved transcription factor binding sites and in general regulatory regions through the analysis of sequences from homologous genes, an approach that is becoming more and more widely used given the ever increasing amount of genomic data available.'),
(91337, 2007, 'bmc', 'Hon-yaku: a biology-driven Bayesian methodology for identifying translation initiation sites in prokaryotes', 'Makita, Yuko|de Hoon, Michiel J L|Danchin, Antoine', 'Unit of Genetics of Bacterial Genomes, Institut Pasteur, URA CNRS 2171, Cedex 15, Paris, France. makita@hgc.jp <makita@hgc.jp>|Unit of Genetics of Bacterial Genomes, Institut Pasteur, URA CNRS 2171, Cedex 15, Paris, France. makita@hgc.jp <makita@hgc.jp>|Unit of Genetics of Bacterial Genomes, Institut Pasteur, URA CNRS 2171, Cedex 15, Paris, France. makita@hgc.jp <makita@hgc.jp>', 'France|France|France', 0, 'Algorithms|Bayes Theorem|Biomimetics|Chromosome Mapping|DNA, Bacterial|Databases, Genetic|Pattern Recognition, Automated|Peptide Chain Initiation, Translational|Protein Biosynthesis|Sequence Analysis, DNA|Software|Systems Biology|Transcription Initiation Site', 'Journal Article', '10.1186/1471-2105-8-47', '17286872', 'Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remains a difficult task. Accurate translation initiation sites (TISs) are important not only for the annotation of unknown proteins but also for the prediction of operons, promoters, and small non-coding RNA genes, as this typically makes use of the intergenic distance. A further problem is that most existing methods are optimized for Escherichia coli data sets, applying these methods to newly sequenced bacterial genomes may not result in an equivalent level of accuracy.'),
(91338, 2007, 'bmc', 'Improved precision and accuracy for microarrays using updated probe set definitions', 'Sandberg, Rickard|Larsson, Ola', 'Massachusetts Institute of Technology, Department of biology, 68-211, Cambridge, MA 02139, USA. sandberg@mit.edu <sandberg@mit.edu>|Massachusetts Institute of Technology, Department of biology, 68-211, Cambridge, MA 02139, USA. sandberg@mit.edu <sandberg@mit.edu>', 'United States|United States', 114, 'Oligonucleotide Array Sequence Analysis|Reverse Transcriptase Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-8-48', '17288599', 'Microarrays enable high throughput detection of transcript expression levels. Different investigators have recently introduced updated probe set definitions to more accurately map probes to our current knowledge of genes and transcripts.'),
(91339, 2007, 'bmc', 'MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments', 'Veyrieras, Jean-Baptiste|Goffinet, Bruno|Charcosset, Alain', 'UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France. veyrieras@moulon.inra.fr|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France. veyrieras@moulon.inra.fr|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France. veyrieras@moulon.inra.fr', 'France|France|France', 109, 'Chromosome Mapping|Computer Graphics|Genetic Markers|Meta-Analysis as Topic|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-49', '17288608', 'Integration of multiple results from Quantitative Trait Loci (QTL) studies is a key point to understand the genetic determinism of complex traits. Up to now many efforts have been made by public database developers to facilitate the storage, compilation and visualization of multiple QTL mapping experiment results. However, studying the congruency between these results still remains a complex task. Presently, the few computational and statistical frameworks to do so are mainly based on empirical methods (e.g. consensus genetic maps are generally built by iterative projection).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91340, 2007, 'bmc', 'BioInfer: a corpus for information extraction in the biomedical domain', 'Pyysalo, Sampo|Ginter, Filip|Heimonen, Juho|Björne, Jari|Boberg, Jorma|Järvinen, Jouni|Salakoski, Tapio', 'Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS), University of Turku, Lemminkäisenkatu 14a, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Database Management Systems|Databases, Factual|Documentation|Genes|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Proteins|RNA|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-8-50', '17291334', 'Lately, there has been a great interest in the application of information extraction methods to the biomedical domain, in particular, to the extraction of relationships of genes, proteins, and RNA from scientific publications. The development and evaluation of such methods requires annotated domain corpora.'),
(91341, 2007, 'bmc', 'msmsEval: tandem mass spectral quality assignment for high-throughput proteomics', 'Wong, Jason W H|Sullivan, Matthew J|Cartwright, Hugh M|Cagney, Gerard', 'Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, South Parks Road, Oxford OX1 3QZ, UK. jason.wong@ucd.ie <jason.wong@ucd.ie>|Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, South Parks Road, Oxford OX1 3QZ, UK. jason.wong@ucd.ie <jason.wong@ucd.ie>|Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, South Parks Road, Oxford OX1 3QZ, UK. jason.wong@ucd.ie <jason.wong@ucd.ie>|Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, South Parks Road, Oxford OX1 3QZ, UK. jason.wong@ucd.ie <jason.wong@ucd.ie>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Gene Expression Profiling|Mass Spectrometry|Models, Chemical|Molecular Sequence Data|Peptide Mapping|Proteome|Proteomics|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-51', '17291342', 'In proteomics experiments, database-search programs are the method of choice for protein identification from tandem mass spectra. As amino acid sequence databases grow however, computing resources required for these programs have become prohibitive, particularly in searches for modified proteins. Recently, methods to limit the number of spectra to be searched based on spectral quality have been proposed by different research groups, but rankings of spectral quality have thus far been based on arbitrary cut-off values. In this work, we develop a more readily interpretable spectral quality statistic by providing probability values for the likelihood that spectra will be identifiable.'),
(91342, 2007, 'bmc', 'PASSIM--an open source software system for managing information in biomedical studies', 'Viksna, Juris|Celms, Edgars|Opmanis, Martins|Podnieks, Karlis|Rucevskis, Peteris|Zarins, Andris|Barrett, Amy|Neogi, Sudeshna Guha|Krestyaninova, Maria|McCarthy, Mark I|Brazma, Alvis|Sarkans, Ugis', 'Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>|Institute of Mathematics and Computer Science, Riga, University of Latvia, Latvia. jviksna@mii.lu.lv <jviksna@mii.lu.lv>', 'Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia|Latvia', 0, 'Artificial Intelligence|Biomedical Engineering|Biomedical Research|Clinical Trials as Topic|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Medical Records Systems, Computerized|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-52', '17291344', 'One of the crucial aspects of day-to-day laboratory information management is collection, storage and retrieval of information about research subjects and biomedical samples. An efficient link between sample data and experiment results is absolutely imperative for a successful outcome of a biomedical study. Currently available software solutions are largely limited to large-scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but often implies sufficient investment of time, effort and funds, which are not always available. There is a clear need for lightweight open source systems for patient and sample information management.'),
(91343, 2007, 'bmc', 'PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results', 'He, Ji|Dai, Xinbin|Zhao, Xuechun', 'Bioinformatics Lab, Plant Biology Division, Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA. jhe@noble.org <jhe@noble.org>|Bioinformatics Lab, Plant Biology Division, Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA. jhe@noble.org <jhe@noble.org>|Bioinformatics Lab, Plant Biology Division, Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA. jhe@noble.org <jhe@noble.org>', 'United States|United States|United States', 0, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-53', '17291345', 'BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming.'),
(91344, 2007, 'bmc', 'BIRCH: a user-oriented, locally-customizable, bioinformatics system', 'Fristensky, Brian', 'Department of Plant Science, University of Manitoba, Winnipeg, Manitoba, R3T 2N2, Canada. frist@cc.umanitoba.ca', 'Canada', 6, 'Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Programming Languages|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-54', '17291351', 'Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists.'),
(91345, 2007, 'bmc', 'In silico identification of NF-kappaB-regulated genes in pancreatic beta-cells', 'Naamane, Najib|van Helden, Jacques|Eizirik, Decio L', 'Laboratory of Experimental Medicine, Université Libre de Bruxelles, Route de Lennik, 808, CP 618, B-1070 Brussels, Belgium. nnaamane@ulb.ac.be <nnaamane@ulb.ac.be>|Laboratory of Experimental Medicine, Université Libre de Bruxelles, Route de Lennik, 808, CP 618, B-1070 Brussels, Belgium. nnaamane@ulb.ac.be <nnaamane@ulb.ac.be>|Laboratory of Experimental Medicine, Université Libre de Bruxelles, Route de Lennik, 808, CP 618, B-1070 Brussels, Belgium. nnaamane@ulb.ac.be <nnaamane@ulb.ac.be>', 'Belgium|Belgium|Belgium', 0, 'Algorithms|Animals|Cytokines|Discriminant Analysis|Gene Expression Profiling|Gene Expression Regulation|Humans|Insulin-Secreting Cells|Mice|Models, Biological|NF-kappa B|Oligonucleotide Array Sequence Analysis|Pan troglodytes|Rats|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-55', '17302974', 'Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1beta and interferon (IFN)-gamma. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1beta-activated transcription factor (TF) nuclear factor (NF)-kappaB, and previous studies by our group have shown that cytokine-induced NF-kappaB activation is pro-apoptotic in beta-cells. To identify NF-kappaB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-kappaB responding genes on the basis of putative regulatory elements.'),
(91346, 2007, 'bmc', 'Recognition of interferon-inducible sites, promoters, and enhancers', 'Ananko, Elena A|Kondrakhin, Yury V|Merkulova, Tatiana I|Kolchanov, Nikolay A', 'Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia. eananko@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia. eananko@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia. eananko@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia. eananko@bionet.nsc.ru', '-|-|-|-', 0, 'Base Sequence|Binding Sites|Chromosome Mapping|Enhancer Elements, Genetic|Interferons|Molecular Sequence Data|Promoter Regions, Genetic|Protein Binding|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1186/1471-2105-8-56', '17309789', 'Computational analysis of gene regulatory regions is important for prediction of functions of many uncharacterized genes. With this in mind, search of the target genes for interferon (IFN) induction appears of interest. IFNs are multi-functional cytokines. Their effects are immunomodulatory, antiviral, antibacterial, and antitumor. The interaction of the IFNs with their cell surface receptors produces an activation of several transcription factors. Four regulatory factors, ISGF3, STAT1, IRF1, and NF-kappaB, are essential for the function of the IFN system. The aim of this work is the development of computational approaches for the recognition of DNA binding sites for these factors and computer programs for the prediction of the IFN-inducible regions.'),
(91347, 2007, 'bmc', 'Understanding and using the meaning of statements in a bio-ontology: recasting the Gene Ontology in OWL', 'Aranguren, Mikel Egaña|Bechhofer, Sean|Lord, Phillip|Sattler, Ulrike|Stevens, Robert', 'School of Computer Science, University of Manchester, Manchester, UK. mikel.eganaaranguren@cs.man.ac.uk <mikel.eganaaranguren@cs.man.ac.uk>|School of Computer Science, University of Manchester, Manchester, UK. mikel.eganaaranguren@cs.man.ac.uk <mikel.eganaaranguren@cs.man.ac.uk>|School of Computer Science, University of Manchester, Manchester, UK. mikel.eganaaranguren@cs.man.ac.uk <mikel.eganaaranguren@cs.man.ac.uk>|School of Computer Science, University of Manchester, Manchester, UK. mikel.eganaaranguren@cs.man.ac.uk <mikel.eganaaranguren@cs.man.ac.uk>|School of Computer Science, University of Manchester, Manchester, UK. mikel.eganaaranguren@cs.man.ac.uk <mikel.eganaaranguren@cs.man.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 34, 'Artificial Intelligence|Computational Biology|Database Management Systems|Databases, Genetic|Genes|Information Storage and Retrieval|Natural Language Processing|Phylogeny|Programming Languages|Proteins|User-Computer Interface', 'Editorial', '10.1186/1471-2105-8-57', '17311682', 'The bio-ontology community falls into two camps: first we have biology domain experts, who actually hold the knowledge we wish to capture in ontologies, second, we have ontology specialists, who hold knowledge about techniques and best practice on ontology development. In the bio-ontology domain, these two camps have often come into conflict, especially where pragmatism comes into conflict with perceived best practice. One of these areas is the insistence of computer scientists on a well-defined semantic basis for the Knowledge Representation language being used. In this article, we will first describe why this community is so insistent. Second, we will illustrate this by examining the semantics of the Web Ontology Language and the semantics placed on the Directed Acyclic Graph as used by the Gene Ontology. Finally we will reconcile the two representations, including the broader Open Biomedical Ontologies format. The ability to exchange between the two representations means that we can capitalise on the features of both languages. Such utility can only arise by the understanding of the semantics of the languages being used. By this illustration of the usefulness of a clear, well-defined language semantics, we wish to promote a wider understanding of the computer science perspective amongst potential users within the biological community.'),
(91348, 2007, 'bmc', 'Sequence similarity is more relevant than species specificity in probabilistic backtranslation', 'Ferro, Alfredo|Giugno, Rosalba|Pigola, Giuseppe|Pulvirenti, Alfredo|Di Pietro, Cinzia|Purrello, Michele|Ragusa, Marco', 'Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 6, 'Algorithms|Codon|Conserved Sequence|Evolution, Molecular|Humans|Models, Statistical|Pattern Recognition, Automated|Protein Biosynthesis|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-58', '17313665', 'Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species.'),
(91349, 2007, 'bmc', 'Bioclipse: an open source workbench for chemo- and bioinformatics', 'Spjuth, Ola|Helmus, Tobias|Willighagen, Egon L|Kuhn, Stefan|Eklund, Martin|Wagener, Johannes|Murray-Rust, Peter|Steinbeck, Christoph|Wikberg, Jarl E S', 'Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ola.spjuth@farmbio.uu.se.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Biochemistry|Computational Biology|Computer Graphics|Genomics|Programming Languages|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-59', '17316423', 'There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no successful attempts have been made to integrate chemo- and bioinformatics into a single framework.'),
(91350, 2007, 'bmc', 'Supervised group Lasso with applications to microarray data analysis', 'Ma, Shuangge|Song, Xiao|Huang, Jian', 'Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA. shuangge.ma@yale.edu|Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA. shuangge.ma@yale.edu|Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA. shuangge.ma@yale.edu', 'United States|United States|United States', 139, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Gene Expression Profiling|Humans|Multigene Family|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-8-60', '17316436', 'A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure.'),
(91351, 2007, 'bmc', 'Factor analysis for gene regulatory networks and transcription factor activity profiles', 'Pournara, Iosifina|Wernisch, Lorenz', 'School of Crystallography, Birkbeck College, University of London, London, UK. i.pournara@cryst.bbk.ac.uk|School of Crystallography, Birkbeck College, University of London, London, UK. i.pournara@cryst.bbk.ac.uk', 'United Kingdom|United Kingdom', 62, 'Algorithms|Bayes Theorem|Computer Simulation|Factor Analysis, Statistical|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1186/1471-2105-8-61', '17319944', 'Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription factors (TFs) are proportional to their mRNA levels. This assumption is invalid for most biological systems. However, one might be able to reconstruct unobserved activity profiles of TFs from the expression profiles of target genes. A simple model is a two-layer network with unobserved TF variables in the first layer and observed gene expression variables in the second layer. TFs are connected to regulated genes by weighted edges. The weights, known as factor loadings, indicate the strength and direction of regulation. Of particular interest are methods that produce sparse networks, networks with few edges, since it is known that most genes are regulated by only a small number of TFs, and most TFs regulate only a small number of genes.'),
(91352, 2007, 'bmc', 'Blast sampling for structural and functional analyses', 'Friedrich, Anne|Ripp, Raymond|Garnier, Nicolas|Bettler, Emmanuel|Deléage, Gilbert|Poch, Olivier|Moulinier, Luc', 'Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>|Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>', 'France|France|France|France|France|France|France', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1186/1471-2105-8-62', '17319945', 'The post-genomic era is characterised by a torrent of biological information flooding the public databases. As a direct consequence, similarity searches starting with a single query sequence frequently lead to the identification of hundreds, or even thousands of potential homologues. The huge volume of data renders the subsequent structural, functional and evolutionary analyses very difficult. It is therefore essential to develop new strategies for efficient sampling of this large sequence space, in order to reduce the number of sequences to be processed. At the same time, it is important to retain the most pertinent sequences for structural and functional studies.'),
(91353, 2007, 'bmc', 'Phylo-mLogo: an interactive and hierarchical multiple-logo visualization tool for alignment of many sequences', 'Shih, Arthur Chun-Chieh|Lee, D T|Peng, Chin-Lin|Wu, Yu-Wei', 'Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. arthur@iis.sinica.edu.tw <arthur@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. arthur@iis.sinica.edu.tw <arthur@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. arthur@iis.sinica.edu.tw <arthur@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. arthur@iis.sinica.edu.tw <arthur@iis.sinica.edu.tw>', '-|-|-|-', 21, 'Algorithms|Animals|Base Sequence|Birds|Data Display|Disease Transmission, Infectious|Gene Expression Profiling|Hemagglutinins|Humans|Influenza in Birds|Molecular Sequence Data|Receptors, Odorant|Sequence Alignment|Sequence Analysis, DNA|Software|Software Validation|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-63', '17319966', 'When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences.'),
(91354, 2007, 'bmc', 'Minimus: a fast, lightweight genome assembler', 'Sommer, Daniel D|Delcher, Arthur L|Salzberg, Steven L|Pop, Mihai', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. dsommer@umiacs.umd.edu <dsommer@umiacs.umd.edu>|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. dsommer@umiacs.umd.edu <dsommer@umiacs.umd.edu>|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. dsommer@umiacs.umd.edu <dsommer@umiacs.umd.edu>|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. dsommer@umiacs.umd.edu <dsommer@umiacs.umd.edu>', 'United States|United States|United States|United States', 274, 'Algorithms|Base Sequence|Chromosome Mapping|DNA|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-64', '17324286', 'Genome assemblers have grown very large and complex in response to the need for algorithms to handle the challenges of large whole-genome sequencing projects. Many of the most common uses of assemblers, however, are best served by a simpler type of assembler that requires fewer software components, uses less memory, and is far easier to install and run.'),
(91355, 2007, 'bmc', 'AGGRESCAN: a server for the prediction and evaluation of hot spots of aggregation in polypeptides', 'Conchillo-Solé, Oscar|de Groot, Natalia S|Avilés, Francesc X|Vendrell, Josep|Daura, Xavier|Ventura, Salvador', 'Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>|Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>|Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>|Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>|Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>|Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain. Oscar.Conhillo@bioinf.uab.cat <Oscar.Conhillo@bioinf.uab.cat>', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Drug Delivery Systems|Humans|Peptides|Predictive Value of Tests|Protein Conformation|Proteins|Software', 'Comparative Study', '10.1186/1471-2105-8-65', '17324296', 'Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimers and Parkinsons diseases. On the biotechnological side, protein production is often hampered by the accumulation of recombinant proteins into aggregates. Thus, the development of methods to anticipate the aggregation properties of polypeptides is receiving increasing attention. AGGRESCAN is a web-based software for the prediction of aggregation-prone segments in protein sequences, the analysis of the effect of mutations on protein aggregation propensities and the comparison of the aggregation properties of different proteins or protein sets.'),
(91356, 2007, 'bmc', 'Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)', 'Hsu, Chun-Nan|Lai, Jin-Mei|Liu, Chia-Hung|Tseng, Huei-Hun|Lin, Chih-Yun|Lin, Kuan-Ting|Yeh, Hsu-Hua|Sung, Ting-Yi|Hsu, Wen-Lian|Su, Li-Jen|Lee, Sheng-An|Chen, Chang-Han|Lee, Gen-Cher|Lee, D T|Shiue, Yow-Ling|Yeh, Chang-Wei|Chang, Chao-Hui|Kao, Cheng-Yan|Huang, Chi-Ying F', 'Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>|Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, ROC. chunnan@iis.sinica.edu.tw <chunnan@iis.sinica.edu.tw>', '-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-', 39, 'Carcinoma, Hepatocellular|Encyclopedias as Topic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Liver Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-66', '17326819', 'The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level.'),
(91357, 2007, 'bmc', 'Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data', 'Zhao, Xin|Cheung, Leo Wang-Kit', 'Department of Information and Computer Sciences, University of Hawaii, 1680 East-West Road, Honolulu, Hawaii 96822, USA. xinz@hawaii.edu <xinz@hawaii.edu>|Department of Information and Computer Sciences, University of Hawaii, 1680 East-West Road, Honolulu, Hawaii 96822, USA. xinz@hawaii.edu <xinz@hawaii.edu>', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Bayes Theorem|Biomarkers, Tumor|Computer Simulation|Diagnosis, Computer-Assisted|Gene Expression Profiling|Models, Biological|Models, Statistical|Neoplasm Proteins|Neoplasms|Normal Distribution|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-67', '17328811', 'Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more important for our understanding of diseases at genomic level. Although many machine learning methods have been developed and applied to the area of microarray gene expression data analysis, the majority of them are based on linear models, which however are not necessarily appropriate for the underlying connection between the target disease and its associated explanatory genes. Linear model based methods usually also bring in false positive significant features more easily. Furthermore, linear model based algorithms often involve calculating the inverse of a matrix that is possibly singular when the number of potentially important genes is relatively large. This leads to problems of numerical instability. To overcome these limitations, a few non-linear methods have recently been introduced to the area. Many of the existing non-linear methods have a couple of critical problems, the model selection problem and the model parameter tuning problem, that remain unsolved or even untouched. In general, a unified framework that allows model parameters of both linear and non-linear models to be easily tuned is always preferred in real-world applications. Kernel-induced learning methods form a class of approaches that show promising potentials to achieve this goal.'),
(91358, 2007, 'bmc', 'False occurrences of functional motifs in protein sequences highlight evolutionary constraints', 'Via, Allegra|Gherardini, Pier Federico|Ferraro, Enrico|Ausiello, Gabriele|Scalia Tomba, Gianpaolo|Helmer-Citterich, Manuela', 'Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it|Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it|Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it|Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it|Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it|Centro di Bioinformatica Molecolare, Department of Biology, University of Rome Tor Vergata, Roma. allegra.via@uniroma2.it', '-|-|-|-|-|-', 7, 'Amino Acid Motifs|Amino Acid Sequence|Evolution, Molecular|False Positive Reactions|Genetic Variation|Molecular Sequence Data|Proteome|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-68', '17331242', 'False occurrences of functional motifs in protein sequences can be considered as random events due solely to the sequence composition of a proteome. Here we use a numerical approach to investigate the random appearance of functional motifs with the aim of addressing biological questions such as: How are organisms protected from undesirable occurrences of motifs otherwise selected for their functionality? Has the random appearance of functional motifs in protein sequences been affected during evolution?'),
(91359, 2007, 'bmc', 'Inference of miRNA targets using evolutionary conservation and pathway analysis', 'Gaidatzis, Dimos|van Nimwegen, Erik|Hausser, Jean|Zavolan, Mihaela', 'Biozentrum, University of Basel, Basel, Switzerland. d.gaidatzis@unibas.ch <d.gaidatzis@unibas.ch>|Biozentrum, University of Basel, Basel, Switzerland. d.gaidatzis@unibas.ch <d.gaidatzis@unibas.ch>|Biozentrum, University of Basel, Basel, Switzerland. d.gaidatzis@unibas.ch <d.gaidatzis@unibas.ch>|Biozentrum, University of Basel, Basel, Switzerland. d.gaidatzis@unibas.ch <d.gaidatzis@unibas.ch>', 'Switzerland|Switzerland|Switzerland|Switzerland', 234, 'Animals|Base Sequence|Conserved Sequence|Evolution, Molecular|Gene Targeting|Humans|MicroRNAs|Molecular Sequence Data|Phylogeny|Protein Biosynthesis|Sequence Alignment|Sequence Analysis, RNA|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-69', '17331257', 'MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially.'),
(91360, 2007, 'bmc', 'Bounds on the distribution of the number of gaps when circles and lines are covered by fragments: theory and practical application to genomic and metagenomic projects', 'Moriarty, John|Marchesi, Julian R|Metcalfe, Anthony', 'Department of Mathematics/Boole Centre for Research in Informatics, University College Cork, Cork, Ireland. jm20@proba.ucc.ie|Department of Mathematics/Boole Centre for Research in Informatics, University College Cork, Cork, Ireland. jm20@proba.ucc.ie|Department of Mathematics/Boole Centre for Research in Informatics, University College Cork, Cork, Ireland. jm20@proba.ucc.ie', 'Ireland|Ireland|Ireland', 3, 'Chromosome Mapping|Computational Biology|Genomic Library|Genomics|Metabolic Networks and Pathways|Poisson Distribution|Research Design|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-8-70', '17335566', 'The question of how a circle or line segment becomes covered when random arcs are marked off has arisen repeatedly in bioinformatics. The number of uncovered gaps is of particular interest. Approximate distributions for the number of gaps have been given in the literature, one motivation being ease of computation. Error bounds for these approximate distributions have not been given.'),
(91361, 2007, 'bmc', 'A comparative study of S/MAR prediction tools', 'Evans, Kenneth|Ott, Sascha|Hansen, Annika|Koentges, Georgy|Wernisch, Lorenz', 'School of Crystallography, Birkbeck College, Malet Street, London, UK. k.evans@mail.cryst.bbk.ac.uk <k.evans@mail.cryst.bbk.ac.uk>|School of Crystallography, Birkbeck College, Malet Street, London, UK. k.evans@mail.cryst.bbk.ac.uk <k.evans@mail.cryst.bbk.ac.uk>|School of Crystallography, Birkbeck College, Malet Street, London, UK. k.evans@mail.cryst.bbk.ac.uk <k.evans@mail.cryst.bbk.ac.uk>|School of Crystallography, Birkbeck College, Malet Street, London, UK. k.evans@mail.cryst.bbk.ac.uk <k.evans@mail.cryst.bbk.ac.uk>|School of Crystallography, Birkbeck College, Malet Street, London, UK. k.evans@mail.cryst.bbk.ac.uk <k.evans@mail.cryst.bbk.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Binding Sites|DNA|Molecular Sequence Data|Nuclear Matrix|Nuclear Matrix-Associated Proteins|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1186/1471-2105-8-71', '17335576', 'S/MARs are regions of the DNA that are attached to the nuclear matrix. These regions are known to affect substantially the expression of genes. The computer prediction of S/MARs is a highly significant task which could contribute to our understanding of chromatin organisation in eukaryotic cells, the number and distribution of boundary elements, and the understanding of gene regulation in eukaryotic cells. However, while a number of S/MAR predictors have been proposed, their accuracy has so far not come under scrutiny.'),
(91362, 2007, 'bmc', 'Visualization of three-way comparisons of omics data', 'Baran, Richard|Robert, Martin|Suematsu, Makoto|Soga, Tomoyoshi|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>', 'Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Computer Graphics|Computer Simulation|Databases, Genetic|Genomics|Humans|Models, Biological|Proteome|Software|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-8-72', '17335588', 'Density plot visualizations (also referred to as heat maps or color maps) are widely used in different fields including large-scale omics studies in biological sciences. However, the current color-codings limit the visualizations to single datasets or pairwise comparisons.'),
(91363, 2007, 'bmc', 'Structural and evolutionary bioinformatics of the SPOUT superfamily of methyltransferases', 'Tkaczuk, Karolina L|Dunin-Horkawicz, Stanislaw|Purta, Elzbieta|Bujnicki, Janusz M', 'Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland. poison-ivy@genesilico.pl <poison-ivy@genesilico.pl>|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland. poison-ivy@genesilico.pl <poison-ivy@genesilico.pl>|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland. poison-ivy@genesilico.pl <poison-ivy@genesilico.pl>|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland. poison-ivy@genesilico.pl <poison-ivy@genesilico.pl>', 'Poland|Poland|Poland|Poland', 0, 'Amino Acid Sequence|Animals|Computational Biology|Evolution, Molecular|Humans|Methyltransferases|Molecular Sequence Data|Multigene Family|Phylogeny|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-73', '17338813', 'SPOUT methyltransferases (MTases) are a large class of S-adenosyl-L-methionine-dependent enzymes that exhibit an unusual alpha/beta fold with a very deep topological knot. In 2001, when no crystal structures were available for any of these proteins, Anantharaman, Koonin, and Aravind identified homology between SpoU and TrmD MTases and defined the SPOUT superfamily. Since then, multiple crystal structures of knotted MTases have been solved and numerous new homologous sequences appeared in the databases. However, no comprehensive comparative analysis of these proteins has been carried out to classify them based on structural and evolutionary criteria and to guide functional predictions.'),
(91364, 2007, 'bmc', 'Gene selection with multiple ordering criteria', 'Chen, James J|Tsai, Chen-An|Tzeng, Shengli|Chen, Chun-Houh', 'Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, USA. jamesJ.chen@fda.hhs.gov|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, USA. jamesJ.chen@fda.hhs.gov|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, USA. jamesJ.chen@fda.hhs.gov|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, USA. jamesJ.chen@fda.hhs.gov', 'United States|United States|United States|United States', 27, 'Algorithms|Colonic Neoplasms|Databases, Genetic|Gene Expression Profiling|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-74', '17338815', 'A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects.'),
(91365, 2007, 'bmc', 'SpliceMiner: a high-throughput database implementation of the NCBI Evidence Viewer for microarray splice variant analysis', 'Kahn, Ari B|Ryan, Michael C|Liu, Hongfang|Zeeberg, Barry R|Jamison, D Curtis|Weinstein, John N', 'Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>|Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>|Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>|Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>|Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>|Department of Bioinformatics, George Mason University, Fairfax, Virginia, USA. arik@mail.nih.gov <arik@mail.nih.gov>', 'United States|United States|United States|United States|United States|United States', 19, 'Alternative Splicing|Databases, Nucleic Acid|Genetic Variation|Genome, Human|Humans|National Library of Medicine (U.S.)|Oligonucleotide Array Sequence Analysis|Software|United States', 'Journal Article', '10.1186/1471-2105-8-75', '17338820', 'There are many fewer genes in the human genome than there are expressed transcripts. Alternative splicing is the reason. Alternatively spliced transcripts are often specific to tissue type, developmental stage, environmental condition, or disease state. Accurate analysis of microarray expression data and design of new arrays for alternative splicing require assessment of probes at the sequence and exon levels.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91366, 2007, 'bmc', 'An efficient grid layout algorithm for biological networks utilizing various biological attributes', 'Kojima, Kaname|Nagasaki, Masao|Jeong, Euna|Kato, Mitsuru|Miyano, Satoru', 'Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. kaname@ims.u-tokyo.ac.jp <kaname@ims.u-tokyo.ac.jp>|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. kaname@ims.u-tokyo.ac.jp <kaname@ims.u-tokyo.ac.jp>|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. kaname@ims.u-tokyo.ac.jp <kaname@ims.u-tokyo.ac.jp>|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. kaname@ims.u-tokyo.ac.jp <kaname@ims.u-tokyo.ac.jp>|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. kaname@ims.u-tokyo.ac.jp <kaname@ims.u-tokyo.ac.jp>', 'Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Computer Simulation|Endothelial Cells|Gene Regulatory Networks|Humans|Models, Biological|Models, Theoretical|Signal Transduction', 'Evaluation Studies', '10.1186/1471-2105-8-76', '17338825', 'Clearly visualized biopathways provide a great help in understanding biological systems. However, manual drawing of large-scale biopathways is time consuming. We proposed a grid layout algorithm that can handle gene-regulatory networks and signal transduction pathways by considering edge-edge crossing, node-edge crossing, distance measure between nodes, and subcellular localization information from Gene Ontology. Consequently, the layout algorithm succeeded in drastically reducing these crossings in the apoptosis model. However, for larger-scale networks, we encountered three problems: (i) the initial layout is often very far from any local optimum because nodes are initially placed at random, (ii) from a biological viewpoint, human layouts still exceed automatic layouts in understanding because except subcellular localization, it does not fully utilize biological information of pathways, and (iii) it employs a local search strategy in which the neighborhood is obtained by moving one node at each step, and automatic layouts suggest that simultaneous movements of multiple nodes are necessary for better layouts, while such extension may face worsening the time complexity.'),
(91367, 2007, 'bmc', 'Comparison of protein structures by growing neighborhood alignments', 'Bhattacharya, Sourangshu|Bhattacharyya, Chiranjib|Chandra, Nagasuma R', 'Dept. of Computer Science and Automation, Indian Institute of Science, Bangalore, India. sourangshu@csa.iisc.ernet.in <sourangshu@csa.iisc.ernet.in>|Dept. of Computer Science and Automation, Indian Institute of Science, Bangalore, India. sourangshu@csa.iisc.ernet.in <sourangshu@csa.iisc.ernet.in>|Dept. of Computer Science and Automation, Indian Institute of Science, Bangalore, India. sourangshu@csa.iisc.ernet.in <sourangshu@csa.iisc.ernet.in>', 'India|India|India', 8, 'Algorithms|Databases, Protein|Protein Folding|Proteins|Sequence Alignment|Structure-Activity Relationship', 'Comparative Study', '10.1186/1471-2105-8-77', '17338826', 'Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure comparison scheme, which is capable of detecting correct alignments even in difficult cases, e.g. non-topological similarities. The proposed method computes protein structure alignments by comparing, small substructures, called neighborhoods. Two different types of neighborhoods, sequence and structure, are defined, and two algorithms arising out of the scheme are detailed. A new method for computing equivalences having non-topological similarities from pairwise similarity score is described. A novel and fast technique for comparing sequence neighborhoods is also developed.'),
(91368, 2007, 'bmc', 'Predicting mostly disordered proteins by using structure-unknown protein data', 'Shimizu, Kana|Muraoka, Yoichi|Hirose, Shuichi|Tomii, Kentaro|Noguchi, Tamotsu', 'Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shimizu-kana@aist.go.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shimizu-kana@aist.go.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shimizu-kana@aist.go.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shimizu-kana@aist.go.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shimizu-kana@aist.go.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-78', '17338828', 'Predicting intrinsically disordered proteins is important in structural biology because they are thought to carry out various cellular functions even though they have no stable three-dimensional structure. We know the structures of far more ordered proteins than disordered proteins. The structural distribution of proteins in nature can therefore be inferred to differ from that of proteins whose structures have been determined experimentally. We know many more protein sequences than we do protein structures, and many of the known sequences can be expected to be those of disordered proteins. Thus it would be efficient to use the information of structure-unknown proteins in order to avoid training data sparseness. We propose a novel method for predicting which proteins are mostly disordered by using spectral graph transducer and training with a huge amount of structure-unknown sequences as well as structure-known sequences.'),
(91369, 2007, 'bmc', 'SBMLeditor: effective creation of models in the Systems Biology Markup language (SBML)', 'Rodriguez, Nicolas|Donizelli, Marco|Le Novère, Nicolas', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rodrigue@ebi.ac.uk <rodrigue@ebi.ac.uk>|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rodrigue@ebi.ac.uk <rodrigue@ebi.ac.uk>|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rodrigue@ebi.ac.uk <rodrigue@ebi.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom', 25, 'Computer Simulation|Models, Biological|Programming Languages|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-79', '17341299', 'The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file.'),
(91370, 2007, 'bmc', 'Bayesian meta-analysis models for microarray data: a comparative study', 'Conlon, Erin M|Song, Joon J|Liu, Anna', 'Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts, USA. econlon@mathstat.umass.edu|Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts, USA. econlon@mathstat.umass.edu|Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts, USA. econlon@mathstat.umass.edu', 'United States|United States|United States', 45, 'Bacillus subtilis|Bayes Theorem|Gene Expression Profiling|Genes, Bacterial|Meta-Analysis as Topic|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-80', '17343745', 'With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods.'),
(91371, 2007, 'bmc', 'TAMEE: data management and analysis for tissue microarrays', 'Thallinger, Gerhard G|Baumgartner, Kerstin|Pirklbauer, Martin|Uray, Martina|Pauritsch, Elke|Mehes, Gabor|Buck, Charles R|Zatloukal, Kurt|Trajanoski, Zlatko', 'Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>|Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria. Gerhard.Thallinger@tugraz.at <Gerhard.Thallinger@tugraz.at>', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 15, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Internet|Software|Tissue Array Analysis|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-81', '17343750', 'With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories.'),
(91372, 2007, 'bmc', 'Cinteny: flexible analysis and visualization of synteny and genome rearrangements in multiple organisms', 'Sinha, Amit U|Meller, Jaroslaw', 'Department of Computer Science, University of Cincinnati, Cincinnati, OH 45221, USA. sinhaam@ececs.uc.edu|Department of Computer Science, University of Cincinnati, Cincinnati, OH 45221, USA. sinhaam@ececs.uc.edu', 'United States|United States', 0, 'Algorithms|Animals|Chromosome Mapping|Chromosomes|Evolution, Molecular|Humans|Mice|Phylogeny|Rats|Sequence Alignment|Sequence Analysis, DNA|Software|Synteny', 'Comparative Study', '10.1186/1471-2105-8-82', '17343765', 'Identifying syntenic regions, i.e., blocks of genes or other markers with evolutionary conserved order, and quantifying evolutionary relatedness between genomes in terms of chromosomal rearrangements is one of the central goals in comparative genomics. However, the analysis of synteny and the resulting assessment of genome rearrangements are sensitive to the choice of a number of arbitrary parameters that affect the detection of synteny blocks. In particular, the choice of a set of markers and the effect of different aggregation strategies, which enable coarse graining of synteny blocks and exclusion of micro-rearrangements, need to be assessed. Therefore, existing tools and resources that facilitate identification, visualization and analysis of synteny need to be further improved to provide a flexible platform for such analysis, especially in the context of multiple genomes.'),
(91373, 2007, 'bmc', 'Orthology prediction at scalable resolution by phylogenetic tree analysis', 'van der Heijden, René T J M|Snel, Berend|van Noort, Vera|Huynen, Martijn A', 'Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 95, 'Algorithms|Biological Evolution|Computer Simulation|Evolution, Molecular|Models, Genetic|Phylogeny|Sensitivity and Specificity|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-8-83', '17346331', 'Orthology is one of the cornerstones of gene function prediction. Dividing the phylogenetic relations between genes into either orthologs or paralogs is however an oversimplification. Already in two-species gene-phylogenies, the complicated, non-transitive nature of phylogenetic relations results in inparalogs and outparalogs. For situations with more than two species we lack semantics to specifically describe the phylogenetic relations, let alone to exploit them. Published procedures to extract orthologous groups from phylogenetic trees do not allow identification of orthology at various levels of resolution, nor do they document the relations between the orthologous groups.'),
(91374, 2007, 'bmc', 'Statistical tests to compare motif count exceptionalities', 'Robin, Stéphane|Schbath, Sophie|Vandewalle, Vincent', 'INA PG/ENGREF/INRA, UMR518 Unité Mathématiques et Informatique Appliquées, 75005 Paris, France. robin@inapg.inra.fr|INA PG/ENGREF/INRA, UMR518 Unité Mathématiques et Informatique Appliquées, 75005 Paris, France. robin@inapg.inra.fr|INA PG/ENGREF/INRA, UMR518 Unité Mathématiques et Informatique Appliquées, 75005 Paris, France. robin@inapg.inra.fr', 'France|France|France', 21, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|Conserved Sequence|DNA, Bacterial|Data Interpretation, Statistical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-8-84', '17346349', 'Finding over- or under-represented motifs in biological sequences is now a common task in genomics. Thanks to p-value calculation for motif counts, exceptional motifs are identified and represent candidate functional motifs. The present work addresses the related question of comparing the exceptionality of one motif in two different sequences. Just comparing the motif count p-values in each sequence is indeed not sufficient to decide if this motif is significantly more exceptional in one sequence compared to the other one. A statistical test is required.'),
(91375, 2007, 'bmc', 'Model based analysis of real-time PCR data from DNA binding dye protocols', 'Alvarez, Mariano J|Vila-Ortiz, Guillermo J|Salibe, Mariano C|Podhajcer, Osvaldo L|Pitossi, Fernando J', 'Gentron Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina. malvarez@c2b2.columbia.edu|Gentron Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina. malvarez@c2b2.columbia.edu|Gentron Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina. malvarez@c2b2.columbia.edu|Gentron Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina. malvarez@c2b2.columbia.edu|Gentron Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina. malvarez@c2b2.columbia.edu', 'Argentina|Argentina|Argentina|Argentina|Argentina', 0, 'Binding Sites|Computer Simulation|DNA|Fluorescent Dyes|Kinetics|Models, Chemical|Models, Genetic|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-85', '17349040', 'Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same.'),
(91376, 2007, 'bmc', 'Towards a comprehensive structural coverage of completed genomes: a structural genomics viewpoint', 'Marsden, Russell L|Lewis, Tony A|Orengo, Christine A', 'Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK. marsden@biochem.ucl.ac.uk|Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK. marsden@biochem.ucl.ac.uk|Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK. marsden@biochem.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 41, 'Animals|Databases, Protein|Genome|Genomics|Humans|Multigene Family|Sequence Analysis, Protein|Structural Homology, Protein', 'Comparative Study', '10.1186/1471-2105-8-86', '17349043', 'Structural genomics initiatives were established with the aim of solving protein structures on a large-scale. For many initiatives, such as the Protein Structure Initiative (PSI), the primary aim of target selection is focussed towards structurally characterising protein families which, so far, lack a structural representative. It is therefore of considerable interest to gain insights into the number and distribution of these families, and what efforts may be required to achieve a comprehensive structural coverage across all protein families.'),
(91377, 2007, 'bmc', 'GeneBins: a database for classifying gene expression data, with application to plant genome arrays', 'Goffard, Nicolas|Weiller, Georg', 'ARC Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra, Australia. nicolas.goffard@anu.edu.au|ARC Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra, Australia. nicolas.goffard@anu.edu.au', 'Australia|Australia', 41, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Genes, Plant|Genome, Plant|Oligonucleotide Array Sequence Analysis|Plants|Software', 'Journal Article', '10.1186/1471-2105-8-87', '17349060', 'To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms.'),
(91378, 2007, 'bmc', 'Regulation of metabolic networks by small molecule metabolites', 'Gutteridge, Alex|Kanehisa, Minoru|Goto, Susumu', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan 611-0011. alexg@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan 611-0011. alexg@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan 611-0011. alexg@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan', 14, 'Animals|Cell Physiological Phenomena|Humans|Metabolic Networks and Pathways', 'Journal Article', '10.1186/1471-2105-8-88', '17352833', 'The ability to regulate metabolism is a fundamental process in living systems. We present an analysis of one of the mechanisms by which metabolic regulation occurs: enzyme inhibition and activation by small molecules. We look at the network properties of this regulatory system and the relationship between the chemical properties of regulatory molecules.'),
(91379, 2007, 'bmc', 'Fast computation of distance estimators', 'Elias, Isaac|Lagergren, Jens', 'Dept. of Numerical Analysis and Computer Science, Royal Institute of Technology, Stockholm, SE-106 91, Sweden. isaac@csc.kth.se|Dept. of Numerical Analysis and Computer Science, Royal Institute of Technology, Stockholm, SE-106 91, Sweden. isaac@csc.kth.se', 'Sweden|Sweden', 8, 'Algorithms|Animals|Computational Biology|DNA Mutational Analysis|Evolution, Molecular|Models, Theoretical|Phylogeny|Time', 'Comparative Study', '10.1186/1471-2105-8-89', '17355623', 'Some distance methods are among the most commonly used methods for reconstructing phylogenetic trees from sequence data. The input to a distance method is a distance matrix, containing estimated pairwise distances between all pairs of taxa. Distance methods themselves are often fast, e.g., the famous and popular Neighbor Joining (NJ) algorithm reconstructs a phylogeny of n taxa in time O(n3). Unfortunately, the fastest practical algorithms known for Computing the distance matrix, from n sequences of length l, takes time proportional to l.n2. Since the sequence length typically is much larger than the number of taxa, the distance estimation is the bottleneck in phylogeny reconstruction. This bottleneck is especially apparent in reconstruction of large phylogenies or in applications where many trees have to be reconstructed, e.g., bootstrapping and genome wide applications.'),
(91380, 2007, 'bmc', 'Importance of data structure in comparing two dimension reduction methods for classification of microarray gene expression data', 'Truntzer, Caroline|Mercier, Catherine|Estève, Jacques|Gautier, Christian|Roy, Pascal', 'CNRS, UMR 5558--Equipe Biostatistique Santé, Villeurbanne, France. caroline.truntzer@chu-lyon.fr|CNRS, UMR 5558--Equipe Biostatistique Santé, Villeurbanne, France. caroline.truntzer@chu-lyon.fr|CNRS, UMR 5558--Equipe Biostatistique Santé, Villeurbanne, France. caroline.truntzer@chu-lyon.fr|CNRS, UMR 5558--Equipe Biostatistique Santé, Villeurbanne, France. caroline.truntzer@chu-lyon.fr|CNRS, UMR 5558--Equipe Biostatistique Santé, Villeurbanne, France. caroline.truntzer@chu-lyon.fr', 'France|France|France|France|France', 0, 'Computer Simulation|Data Interpretation, Statistical|Electronic Data Processing|Humans|Leukemia|Lymphoma, Large B-Cell, Diffuse|Male|Models, Biological|Oligonucleotide Array Sequence Analysis|Phenotype|Prostatic Neoplasms', 'Comparative Study', '10.1186/1471-2105-8-90', '17355634', 'With the advance of microarray technology, several methods for gene classification and prognosis have been already designed. However, under various denominations, some of these methods have similar approaches. This study evaluates the influence of gene expression variance structure on the performance of methods that describe the relationship between gene expression levels and a given phenotype through projection of data onto discriminant axes.'),
(91381, 2007, 'bmc', 'Modeling human cancer-related regulatory modules by GA-RNN hybrid algorithms', 'Chiang, Jung-Hsien|Chao, Shih-Yi', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tanian, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tanian, Taiwan. jchiang@mail.ncku.edu.tw', '-|-', 22, 'Algorithms|Binding Sites|Computer Simulation|DNA, Neoplasm|Humans|Models, Genetic|Neoplasm Proteins|Neoplasms|Neural Networks (Computer)|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors|Transcriptional Activation', 'Evaluation Studies', '10.1186/1471-2105-8-91', '17359522', 'Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as developments of new diagnose and therapies. Several mathematical models have been used to explore the phenomena of transcriptional regulatory mechanisms in Saccharomyces cerevisiae. However, the contemplating on controlling of feed-forward and feedback loops in transcriptional regulatory mechanisms is not resolved adequately in Saccharomyces cerevisiae, nor is in human cancer cells.'),
(91382, 2007, 'bmc', 'Discarding duplicate ditags in LongSAGE analysis may introduce significant error', 'Emmersen, Jeppe|Heidenblut, Anna M|Høgh, Annabeth Laursen|Hahn, Stephan A|Welinder, Karen G|Nielsen, Kåre L', 'Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>|Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>|Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>|Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>|Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>|Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University, Aalborg, Denmark. je@bio.aau.dk <je@bio.aau.dk>', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 8, 'Algorithms|Base Sequence|Expressed Sequence Tags|Gene Expression Regulation|Software', 'Journal Article', '10.1186/1471-2105-8-92', '17359537', 'During gene expression analysis by Serial Analysis of Gene Expression (SAGE), duplicate ditags are routinely removed from the data analysis, because they are suspected to stem from artifacts during SAGE library construction. As a consequence, naturally occurring duplicate ditags are also removed from the analysis leading to an error of measurement.'),
(91383, 2007, 'bmc', 'Normalization method for metabolomics data using optimal selection of multiple internal standards', 'Sysi-Aho, Marko|Katajamaa, Mikko|Yetukuri, Laxman|Oresic, Matej', 'VTT Technical Research Centre of Finland, Tietotie 2, FIN-02044 VTT, Espoo, Finland. marko.sysi-aho@vtt.fi <marko.sysi-aho@vtt.fi>|VTT Technical Research Centre of Finland, Tietotie 2, FIN-02044 VTT, Espoo, Finland. marko.sysi-aho@vtt.fi <marko.sysi-aho@vtt.fi>|VTT Technical Research Centre of Finland, Tietotie 2, FIN-02044 VTT, Espoo, Finland. marko.sysi-aho@vtt.fi <marko.sysi-aho@vtt.fi>|VTT Technical Research Centre of Finland, Tietotie 2, FIN-02044 VTT, Espoo, Finland. marko.sysi-aho@vtt.fi <marko.sysi-aho@vtt.fi>', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Databases, Protein|Gene Expression|Gene Expression Profiling|Models, Biological|Proteome|Reference Values', 'Journal Article', '10.1186/1471-2105-8-93', '17362505', 'Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task.'),
(91384, 2007, 'bmc', 'Non-coding sequence retrieval system for comparative genomic analysis of gene regulatory elements', 'Doh, Sung Tae|Zhang, Yunyu|Temple, Matthew H|Cai, Li', 'Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. sungtae@rci.rutgers.edu <sungtae@rci.rutgers.edu>|Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. sungtae@rci.rutgers.edu <sungtae@rci.rutgers.edu>|Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. sungtae@rci.rutgers.edu <sungtae@rci.rutgers.edu>|Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. sungtae@rci.rutgers.edu <sungtae@rci.rutgers.edu>', 'United States|United States|United States|United States', 10, 'Algorithms|Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Genetic|Humans|Information Storage and Retrieval|Molecular Sequence Data|RNA, Untranslated|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-94', '17362514', 'Completion of the human genome sequence along with other species allows for greater understanding of the biochemical mechanisms and processes that govern healthy as well as diseased states. The large size of the genome sequences has made them difficult to study using traditional methods. There are many studies focusing on the protein coding sequences, however, not much is known about the function of non-coding regions of the genome. It has been demonstrated that parts of the non-coding region play a critical role as gene regulatory elements. Enhancers that regulate transcription processes have been found in intergenic regions. Furthermore, it is observed that regulatory elements found in non-coding regions are highly conserved across different species. However, the analysis of these regulatory elements is not as straightforward as it may first seem. The development of a centralized resource that allows for the quick and easy retrieval of non-coding sequences from multiple species and is capable of handling multi-gene queries is critical for the analysis of non-coding sequences. Here we describe the development of a web-based non-coding sequence retrieval system.'),
(91385, 2007, 'bmc', 'The reactive metabolite target protein database (TPDB)--a web-accessible resource', 'Hanzlik, Robert P|Koen, Yakov M|Theertham, Bhargav|Dong, Yinghua|Fang, Jianwen', 'Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045, USA. rhanzlik@ku.edu|Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045, USA. rhanzlik@ku.edu|Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045, USA. rhanzlik@ku.edu|Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045, USA. rhanzlik@ku.edu|Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045, USA. rhanzlik@ku.edu', 'United States|United States|United States|United States|United States', 29, 'Binding Sites|Database Management Systems|Databases, Protein|Drug Delivery Systems|Information Storage and Retrieval|Internet|Protein Binding|Proteins|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-95', '17367530', 'The toxic effects of many simple organic compounds stem from their biotransformation to chemically reactive metabolites which bind covalently to cellular proteins. To understand the mechanisms of cytotoxic responses it may be important to know which proteins become adducted and whether some may be common targets of multiple toxins. The literature of this field is widely scattered but expanding rapidly, suggesting the need for a comprehensive, searchable database of reactive metabolite target proteins.'),
(91386, 2007, 'bmc', 'Linear array of conserved sequence motifs to discriminate protein subfamilies: study on pyridine nucleotide-disulfide reductases', 'Avila, César L|Rapisarda, Viviana A|Farías, Ricardo N|De Las Rivas, Javier|Chehín, Rosana', 'Departamento Bioquímica de la Nutrición, Instituto Superior de Investigaciones Biológicas (CONICET-UNT), San Miguel de Tucumán, Tucumán, Argentina. cavila@fbqf.unt.edu.ar <cavila@fbqf.unt.edu.ar>|Departamento Bioquímica de la Nutrición, Instituto Superior de Investigaciones Biológicas (CONICET-UNT), San Miguel de Tucumán, Tucumán, Argentina. cavila@fbqf.unt.edu.ar <cavila@fbqf.unt.edu.ar>|Departamento Bioquímica de la Nutrición, Instituto Superior de Investigaciones Biológicas (CONICET-UNT), San Miguel de Tucumán, Tucumán, Argentina. cavila@fbqf.unt.edu.ar <cavila@fbqf.unt.edu.ar>|Departamento Bioquímica de la Nutrición, Instituto Superior de Investigaciones Biológicas (CONICET-UNT), San Miguel de Tucumán, Tucumán, Argentina. cavila@fbqf.unt.edu.ar <cavila@fbqf.unt.edu.ar>|Departamento Bioquímica de la Nutrición, Instituto Superior de Investigaciones Biológicas (CONICET-UNT), San Miguel de Tucumán, Tucumán, Argentina. cavila@fbqf.unt.edu.ar <cavila@fbqf.unt.edu.ar>', 'Argentina|Argentina|Argentina|Argentina|Argentina', 8, 'Amino Acid Motifs|Amino Acid Sequence|Computer Simulation|Conserved Sequence|Discriminant Analysis|Disulfides|Linear Models|Models, Chemical|Molecular Sequence Data|Nucleotides|Oxidoreductases|Pyridines|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-8-96', '17367536', 'The pyridine nucleotide disulfide reductase (PNDR) is a large and heterogeneous protein family divided into two classes (I and II), which reflect the divergent evolution of its characteristic disulfide redox active site. However, not all the PNDR members fit into these categories and this suggests the need of further studies to achieve a more comprehensive classification of this complex family.'),
(91387, 2007, 'bmc', 'MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes', 'Zhu, Huaiqiu|Hu, Gang-Qing|Yang, Yi-Fan|Wang, Jin|She, Zhen-Su', 'State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. hqzhu@pku.edu.cn <hqzhu@pku.edu.cn>|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. hqzhu@pku.edu.cn <hqzhu@pku.edu.cn>|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. hqzhu@pku.edu.cn <hqzhu@pku.edu.cn>|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. hqzhu@pku.edu.cn <hqzhu@pku.edu.cn>|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. hqzhu@pku.edu.cn <hqzhu@pku.edu.cn>', 'China|China|China|China|China', 40, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Genome, Archaeal|Genome, Bacterial|Open Reading Frames|Pattern Recognition, Automated|Prokaryotic Initiation Factors|Proteome|Software', 'Evaluation Studies', '10.1186/1471-2105-8-97', '17367537', 'Despite a remarkable success in the computational prediction of genes in Bacteria and Archaea, a lack of comprehensive understanding of prokaryotic gene structures prevents from further elucidation of differences among genomes. It continues to be interesting to develop new ab initio algorithms which not only accurately predict genes, but also facilitate comparative studies of prokaryotic genomes.'),
(91388, 2007, 'bmc', 'Including probe-level uncertainty in model-based gene expression clustering', 'Liu, Xuejun|Lin, Kevin K|Andersen, Bogi|Rattray, Magnus', 'College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 210016, China. xuejun.liu@nuaa.edu.cn <xuejun.liu@nuaa.edu.cn>|College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 210016, China. xuejun.liu@nuaa.edu.cn <xuejun.liu@nuaa.edu.cn>|College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 210016, China. xuejun.liu@nuaa.edu.cn <xuejun.liu@nuaa.edu.cn>|College of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 210016, China. xuejun.liu@nuaa.edu.cn <xuejun.liu@nuaa.edu.cn>', 'China|China|China|China', 0, 'Algorithms|Artifacts|Cluster Analysis|DNA Probes|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Normal Distribution|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-98', '17376221', 'Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the exploration of unknown gene functions. Microarray experiments are associated with many sources of experimental and biological variation and the resulting gene expression data are therefore very noisy. Many heuristic and model-based clustering approaches have been developed to cluster this noisy data. However, few of them include consideration of probe-level measurement error which provides rich information about technical variability.'),
(91389, 2007, 'bmc', 'In silico segmentations of lentivirus envelope sequences', 'Boissin-Quillon, Aurélia|Piau, Didier|Leroux, Caroline', 'UMR754 INRA-ENVL-UCBL Rétrovirus et Pathologie Comparée, IFR 128 BioSciences Lyon-Gerland, Université Claude Bernard Lyon 1, Lyon, France. aurelia.quillon@univ-lyon1.fr <aurelia.quillon@univ-lyon1.fr>|UMR754 INRA-ENVL-UCBL Rétrovirus et Pathologie Comparée, IFR 128 BioSciences Lyon-Gerland, Université Claude Bernard Lyon 1, Lyon, France. aurelia.quillon@univ-lyon1.fr <aurelia.quillon@univ-lyon1.fr>|UMR754 INRA-ENVL-UCBL Rétrovirus et Pathologie Comparée, IFR 128 BioSciences Lyon-Gerland, Université Claude Bernard Lyon 1, Lyon, France. aurelia.quillon@univ-lyon1.fr <aurelia.quillon@univ-lyon1.fr>', 'France|France|France', 1, 'Algorithms|Animals|Conserved Sequence|Genetic Variation|Humans|Lentivirus|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity|Viral Envelope Proteins', 'Journal Article', '10.1186/1471-2105-8-99', '17376229', 'The gene encoding the envelope of lentiviruses exhibits a considerable plasticity, particularly the region which encodes the surface (SU) glycoprotein. Interestingly, mutations do not appear uniformly along the sequence of SU, but they are clustered in restricted areas, called variable (V) regions, which are interspersed with relatively more stable regions, called constant (C) regions. We look for specific signatures of C/V regions, using hidden Markov models constructed with SU sequences of the equine, human, small ruminant and simian lentiviruses.'),
(91390, 2007, 'bmc', 'MotifCombinator: a web-based tool to search for combinations of cis-regulatory motifs', 'Kato, Mamoru|Tsunoda, Tatsuhiko', 'Laboratory for Medical Informatics, SNP Research Center, RIKEN, Yokohama, Japan. kato@src.riken.jp|Laboratory for Medical Informatics, SNP Research Center, RIKEN, Yokohama, Japan. kato@src.riken.jp', 'Japan|Japan', 0, 'Amino Acid Motifs|Databases, Genetic|Gene Expression Regulation|Internet|Oligonucleotide Array Sequence Analysis|Regulatory Sequences, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-8-100', '17378935', 'A combination of multiple types of transcription factors and cis-regulatory elements is often required for gene expression in eukaryotes, and the combinatorial regulation confers specific gene expression to tissues or environments. To reveal the combinatorial regulation, computational methods are developed that efficiently infer combinations of cis-regulatory motifs that are important for gene expression as measured by DNA microarrays. One promising type of computational method is to utilize regression analysis between expression levels and scores of motifs in input sequences. This type takes full advantage of information on expression levels because it does not require that the expression level of each gene be dichotomized according to whether or not it reaches a certain threshold level. However, there is no web-based tool that employs regression methods to systematically search for motif combinations and that practically handles combinations of more than two or three motifs.'),
(91391, 2007, 'bmc', 'LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise', 'Mantini, Dante|Petrucci, Francesca|Pieragostino, Damiana|Del Boccio, Piero|Di Nicola, Marta|Di Ilio, Carmine|Federici, Giorgio|Sacchetta, Paolo|Comani, Silvia|Urbani, Andrea', 'Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>|Istituto Tecnologie Avanzate Biomediche, Fondazione G. DAnnunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 85, 'Adult|Computational Biology|Electricity|Humans|Proteins|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1186/1471-2105-8-101', '17386085', 'Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances.'),
(91392, 2007, 'bmc', 'SAMPI: protein identification with mass spectra alignments', 'Kaltenbach, Hans-Michael|Wilke, Andreas|Böcker, Sebastian', 'AG Genominformatik, Technische Fakultät, Universität Bielefeld, Bielefeld, Germany. michael@cebitec.uni-bielefeld.de|AG Genominformatik, Technische Fakultät, Universität Bielefeld, Bielefeld, Germany. michael@cebitec.uni-bielefeld.de|AG Genominformatik, Technische Fakultät, Universität Bielefeld, Bielefeld, Germany. michael@cebitec.uni-bielefeld.de', 'Germany|Germany|Germany', 0, 'Corynebacterium glutamicum|Databases, Protein|Mass Spectrometry|Peptide Mapping|Peptides|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1186/1471-2105-8-102', '17386090', 'Mass spectrometry based peptide mass fingerprints (PMFs) offer a fast, efficient, and robust method for protein identification. A protein is digested (usually by trypsin) and its mass spectrum is compared to simulated spectra for protein sequences in a database. However, existing tools for analyzing PMFs often suffer from missing or heuristic analysis of the significance of search results and insufficient handling of missing and additional peaks.'),
(91393, 2007, 'bmc', 'Modeling biochemical transformation processes and information processing with Narrator', 'Mandel, Johannes J|Fuss, Hendrik|Palfreyman, Niall M|Dubitzky, Werner', 'Dept, of Biotechnology & Bioinformatics, Weihenstephan University of Applied Sciences, 85350 Freising, Germany. johannes.mandel@fh-weihenstephan.de|Dept, of Biotechnology & Bioinformatics, Weihenstephan University of Applied Sciences, 85350 Freising, Germany. johannes.mandel@fh-weihenstephan.de|Dept, of Biotechnology & Bioinformatics, Weihenstephan University of Applied Sciences, 85350 Freising, Germany. johannes.mandel@fh-weihenstephan.de|Dept, of Biotechnology & Bioinformatics, Weihenstephan University of Applied Sciences, 85350 Freising, Germany. johannes.mandel@fh-weihenstephan.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Biochemistry|Computer Graphics|Computer Simulation|Information Storage and Retrieval|Information Theory|Models, Biological|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-103', '17389034', 'Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing.'),
(91394, 2007, 'bmc', 'HMM-ModE--improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences', 'Srivastava, Prashant K|Desai, Dhwani K|Nandi, Soumyadeep|Lynn, Andrew M', 'School of Information Technology, Jawaharlal Nehru University, New Delhi, India. prashant.k.srivastava@gmail.com <prashant.k.srivastava@gmail.com>|School of Information Technology, Jawaharlal Nehru University, New Delhi, India. prashant.k.srivastava@gmail.com <prashant.k.srivastava@gmail.com>|School of Information Technology, Jawaharlal Nehru University, New Delhi, India. prashant.k.srivastava@gmail.com <prashant.k.srivastava@gmail.com>|School of Information Technology, Jawaharlal Nehru University, New Delhi, India. prashant.k.srivastava@gmail.com <prashant.k.srivastava@gmail.com>', 'India|India|India|India', 28, 'Algorithms|Artificial Intelligence|Data Interpretation, Statistical|Discriminant Analysis|Markov Chains|Models, Chemical|Models, Statistical|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-8-104', '17389042', 'Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have been used in identifying remote homologues with considerable success. These conservation patterns arise from fold specific signals, shared across multiple families, and function specific signals unique to the families. The availability of sequences pre-classified according to their function permits the use of negative training sequences to improve the specificity of the HMM, both by optimizing the threshold cutoff and by modifying emission probabilities to minimize the influence of fold-specific signals. A protocol to generate family specific HMMs is described that first constructs a profile HMM from an alignment of the familys sequences and then uses this model to identify sequences belonging to other classes that score above the default threshold (false positives). Ten-fold cross validation is used to optimise the discrimination threshold score for the model. The advent of fast multiple alignment methods enables the use of the profile alignments to align the true and false positive sequences, and the resulting alignments are used to modify the emission probabilities in the original model.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91395, 2007, 'bmc', 'Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry', 'Kind, Tobias|Fiehn, Oliver', 'University of California Davis, Genome Center, Davis, CA 95616, USA. tkind@ucdavis.edu <tkind@ucdavis.edu>|University of California Davis, Genome Center, Davis, CA 95616, USA. tkind@ucdavis.edu <tkind@ucdavis.edu>', 'United States|United States', 664, 'Algorithms|Biopolymers|Computer Simulation|Mass Spectrometry|Models, Chemical|Organic Chemicals', 'Journal Article', '10.1186/1471-2105-8-105', '17389044', 'Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas.'),
(91396, 2007, 'bmc', 'Discovering structural motifs using a structural alphabet: application to magnesium-binding sites', 'Dudev, Minko|Lim, Carmay', 'Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan. frater_ia@yahoo.com <frater_ia@yahoo.com>|Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan. frater_ia@yahoo.com <frater_ia@yahoo.com>', '-|-', 51, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Databases, Protein|Magnesium|Metalloproteins|Molecular Sequence Data|Protein Binding|Protein Structure, Secondary', 'Journal Article', '10.1186/1471-2105-8-106', '17389049', 'For many metalloproteins, sequence motifs characteristic of metal-binding sites have not been found or are so short that they would not be expected to be metal-specific. Striking examples of such metalloproteins are those containing Mg2+, one of the most versatile metal cofactors in cellular biochemistry. Even when Mg2+-proteins share insufficient sequence homology to identify Mg2+-specific sequence motifs, they may still share similarity in the Mg2+-binding site structure. However, no structural motifs characteristic of Mg2+-binding sites have been reported. Thus, our aims are (i) to develop a general method for discovering structural patterns/motifs characteristic of ligand-binding sites, given the 3D protein structures, and (ii) to apply it to Mg2+-proteins sharing <30% sequence identity. Our motif discovery method employs structural alphabet encoding to convert 3D structures to the corresponding 1D structural letter sequences, where the Mg2+-structural motifs are identified as recurring structural patterns.'),
(91397, 2007, 'bmc', 'Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes', 'Rasmussen, John P|Saint, Christopher P|Monis, Paul T', 'Cooperative Research Centre for Water Quality and Treatment, Australian Water Quality Centre, SA Water Corporation, Salisbury, SA, Australia. paul.rasmussen@sawater.com.au|Cooperative Research Centre for Water Quality and Treatment, Australian Water Quality Centre, SA Water Corporation, Salisbury, SA, Australia. paul.rasmussen@sawater.com.au|Cooperative Research Centre for Water Quality and Treatment, Australian Water Quality Centre, SA Water Corporation, Salisbury, SA, Australia. paul.rasmussen@sawater.com.au', 'Australia|Australia|Australia', 44, 'Animals|Computer Simulation|Cyanobacteria|DNA|DNA Probes|Eukaryota|Fluorescent Dyes|Intercalating Agents|Models, Chemical|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Software Validation|Transition Temperature', 'Evaluation Studies', '10.1186/1471-2105-8-107', '17391531', 'DNA melting curve analysis using double-stranded DNA-specific dyes such as SYTO9 produce complex and reproducible melting profiles, resulting in the detection of multiple melting peaks from a single amplicon and allowing the discrimination of different species. We compare the melting curves of several Naegleria and Cryptosporidium amplicons generated in vitro with in silico DNA melting simulations using the programs POLAND and MELTSIM., then test the utility of these programs for assay design using a genetic marker for toxin production in cyanobacteria.'),
(91398, 2007, 'bmc', 'Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: high-resolution annotation for microarrays', 'Lu, Jun|Lee, Joseph C|Salit, Marc L|Cam, Margaret C', 'Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 USA. lujun@mail.nih.gov <lujun@mail.nih.gov>|Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 USA. lujun@mail.nih.gov <lujun@mail.nih.gov>|Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 USA. lujun@mail.nih.gov <lujun@mail.nih.gov>|Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 USA. lujun@mail.nih.gov <lujun@mail.nih.gov>', 'United States|United States|United States|United States', 44, 'Chromosome Mapping|Databases, Genetic|Documentation|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sensitivity and Specificity|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-108', '17394657', 'Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described, however, few studies have provided rigorous solutions for routine data analysis.'),
(91399, 2007, 'bmc', 'A meta-data based method for DNA microarray imputation', 'Jörnsten, Rebecka|Ouyang, Ming|Wang, Hui-Yu', 'Department of Statistics, Rutgers, the State University of New Jersey, New Brunswick, NJ 08903, USA. rebecka@stat.rutgers.edu <rebecka@stat.rutgers.edu>|Department of Statistics, Rutgers, the State University of New Jersey, New Brunswick, NJ 08903, USA. rebecka@stat.rutgers.edu <rebecka@stat.rutgers.edu>|Department of Statistics, Rutgers, the State University of New Jersey, New Brunswick, NJ 08903, USA. rebecka@stat.rutgers.edu <rebecka@stat.rutgers.edu>', 'Jersey|Jersey|Jersey', 13, 'Algorithms|Artifacts|Computer Simulation|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Meta-Analysis as Topic|Models, Biological|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Evaluation Studies', '10.1186/1471-2105-8-109', '17394658', 'DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting.'),
(91400, 2007, 'bmc', 'Fast automated cell phenotype image classification', 'Hamilton, Nicholas A|Pantelic, Radosav S|Hanson, Kelly|Teasdale, Rohan D', 'ARC Centre in Bioinformatics, University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au|ARC Centre in Bioinformatics, University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au|ARC Centre in Bioinformatics, University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au|ARC Centre in Bioinformatics, University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au', 'Australia|Australia|Australia|Australia', 111, 'Computational Biology|Image Processing, Computer-Assisted|Phenotype|Software|Subcellular Fractions', 'Journal Article', '10.1186/1471-2105-8-110', '17394669', 'The genomic revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a proteins sub-cellular localisation is proving invaluable, and recent advances in automated fluorescent microscopy allow protein localisations to be imaged in high throughput. Hence there is a need for large scale automated computational techniques to efficiently quantify, distinguish and classify sub-cellular images. While image statistics have proved highly successful in distinguishing localisation, commonly used measures suffer from being relatively slow to compute, and often require cells to be individually selected from experimental images, thus limiting both throughput and the range of potential applications. Here we introduce threshold adjacency statistics, the essence which is to threshold the image and to count the number of above threshold pixels with a given number of above threshold pixels adjacent. These novel measures are shown to distinguish and classify images of distinct sub-cellular localization with high speed and accuracy without image cropping.'),
(91401, 2007, 'bmc', 'Evaluation of gene-expression clustering via mutual information distance measure', 'Priness, Ido|Maimon, Oded|Ben-Gal, Irad', 'Department of Industrial Engineering, Tel Aviv University, Israel. ido.priness@gmail.com <ido.priness@gmail.com>|Department of Industrial Engineering, Tel Aviv University, Israel. ido.priness@gmail.com <ido.priness@gmail.com>|Department of Industrial Engineering, Tel Aviv University, Israel. ido.priness@gmail.com <ido.priness@gmail.com>', 'Israel|Israel|Israel', 109, 'Algorithms|Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-111', '17397530', 'The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI) measure versus the use of the well known Euclidean distance and Pearson correlation coefficient.'),
(91402, 2007, 'bmc', 'Locational distribution of gene functional classes in Arabidopsis thaliana', 'Riley, Michael C|Clare, Amanda|King, Ross D', 'Department of Computer Science, University of Wales, Aberystwyth, Penglais, Aberystwyth, Ceredigion, Wales, UK. mcr04@aber.ac.uk <mcr04@aber.ac.uk>|Department of Computer Science, University of Wales, Aberystwyth, Penglais, Aberystwyth, Ceredigion, Wales, UK. mcr04@aber.ac.uk <mcr04@aber.ac.uk>|Department of Computer Science, University of Wales, Aberystwyth, Penglais, Aberystwyth, Ceredigion, Wales, UK. mcr04@aber.ac.uk <mcr04@aber.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom', 7, 'Arabidopsis|Chromosome Mapping|Genome, Plant|Linkage Disequilibrium|Multigene Family|Tandem Repeat Sequences', 'Journal Article', '10.1186/1471-2105-8-112', '17397552', 'We are interested in understanding the locational distribution of genes and their functions in genomes, as this distribution has both functional and evolutionary significance. Gene locational distribution is known to be affected by various evolutionary processes, with tandem duplication thought to be the main process producing clustering of homologous sequences. Recent research has found clustering of protein structural families in the human genome, even when genes identified as tandem duplicates have been removed from the data. However, this previous research was hindered as they were unable to analyse small sample sizes. This is a challenge for bioinformatics as more specific functional classes have fewer examples and conventional statistical analyses of these small data sets often produces unsatisfactory results.'),
(91403, 2007, 'bmc', 'Improved residue contact prediction using support vector machines and a large feature set', 'Cheng, Jianlin|Baldi, Pierre', 'School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA. jianlin.cheng@gmail.com|School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA. jianlin.cheng@gmail.com', 'United States|United States', 166, 'Algorithms|Amino Acids|Artificial Intelligence|Binding Sites|Computer Simulation|Databases, Protein|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-8-113', '17407573', 'Predicting protein residue-residue contacts is an important 2D prediction task. It is useful for ab initio structure prediction and understanding protein folding. In spite of steady progress over the past decade, contact prediction remains still largely unsolved.'),
(91404, 2007, 'bmc', 'From genes to functional classes in the study of biological systems', 'Al-Shahrour, Fátima|Arbiza, Leonardo|Dopazo, Hernán|Huerta-Cepas, Jaime|Mínguez, Pablo|Montaner, David|Dopazo, Joaquín', 'Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>|Bioinformatics Department, Valencia, Spain. falshahrour@cipf.es <falshahrour@cipf.es>', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 93, 'Algorithms|Chromosome Mapping|Computer Simulation|Gene Expression Profiling|Models, Biological|Multigene Family|Signal Transduction|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-114', '17407596', 'With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed.'),
(91405, 2007, 'bmc', 'Dependence of paracentric inversion rate on tract length', 'York, Thomas L|Durrett, Rick|Nielsen, Rasmus', 'Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, USA. tly2@cornell.edu|Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, USA. tly2@cornell.edu|Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, USA. tly2@cornell.edu', 'United States|United States|United States', 7, 'Animals|Chromosome Inversion|Chromosome Mapping|Drosophila|Gene Frequency|Genetic Markers|Introns', 'Journal Article', '10.1186/1471-2105-8-115', '17407601', 'We develop a Bayesian method based on MCMC for estimating the relative rates of pericentric and paracentric inversions from marker data from two species. The method also allows estimation of the distribution of inversion tract lengths.'),
(91406, 2007, 'bmc', 'ASH structure alignment package: sensitivity and selectivity in domain classification', 'Standley, Daron M|Toh, Hiroyuki|Nakamura, Haruki', 'Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, Japan. standley@protein.osaka-u.ac.jp|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, Japan. standley@protein.osaka-u.ac.jp|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, Japan. standley@protein.osaka-u.ac.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-8-116', '17407606', 'Structure alignment methods offer the possibility of measuring distant evolutionary relationships between proteins that are not visible by sequence-based analysis. However, the question of how structural differences and similarities ought to be quantified in this regard remains open. In this study we construct a training set of sequence-unique CATH and SCOP domains, from which we develop a scoring function that can reliably identify domains with the same CATH topology and SCOP fold classification. The score is implemented in the ASH structure alignment package, for which the source code and a web service are freely available from the PDBj website http://www.pdbj.org/ASH/.'),
(91407, 2007, 'bmc', 'Colony size measurement of the yeast gene deletion strains for functional genomics', 'Memarian, Negar|Jessulat, Matthew|Alirezaie, Javad|Mir-Rashed, Nadereh|Xu, Jianhua|Zareie, Mehri|Smith, Myron|Golshani, Ashkan', 'Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>|Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada. nmemarian@comm.utoronto.ca <nmemarian@comm.utoronto.ca>', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Cell Cycle Proteins|Cell Proliferation|Chromosome Mapping|Colony Count, Microbial|Computer Simulation|DNA Repair|Gene Deletion|Genomics|MAP Kinase Kinase 1|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Schizosaccharomyces pombe Proteins|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-117', '17408490', 'Numerous functional genomics approaches have been developed to study the model organism yeast, Saccharomyces cerevisiae, with the aim of systematically understanding the biology of the cell. Some of these techniques are based on yeast growth differences under different conditions, such as those generated by gene mutations, chemicals or both. Manual inspection of the yeast colonies that are grown under different conditions is often used as a method to detect such growth differences.'),
(91408, 2007, 'bmc', 'Meta-analysis of several gene lists for distinct types of cancer: a simple way to reveal common prognostic markers', 'Yang, Xinan|Sun, Xiao', 'State Key Laboratory of Bioelectronics, Southeast University, Nanjing, PR China. xnyang@seu.edu.cn|State Key Laboratory of Bioelectronics, Southeast University, Nanjing, PR China. xnyang@seu.edu.cn', 'China|China', 20, 'Algorithms|Biomarkers, Tumor|Databases, Protein|Diagnosis, Computer-Assisted|Humans|Information Storage and Retrieval|Meta-Analysis as Topic|Neoplasm Proteins|Neoplasms|Pattern Recognition, Automated|Prognosis', 'Evaluation Studies', '10.1186/1471-2105-8-118', '17411443', 'Although prognostic biomarkers specific for particular cancers have been discovered, microarray analysis of gene expression profiles, supported by integrative analysis algorithms, helps to identify common factors in molecular oncology. Similarities of Ordered Gene Lists (SOGL) is a recently proposed approach to meta-analysis suitable for identifying features shared by two data sets. Here we extend the idea of SOGL to the detection of significant prognostic marker genes from microarrays of multiple data sets. Three data sets for leukemia and the other six for different solid tumors are used to demonstrate our method, using established statistical techniques.'),
(91409, 2007, 'bmc', 'Selective prediction of interaction sites in protein structures with THEMATICS', 'Wei, Ying|Ko, Jaeju|Murga, Leonel F|Ondrechen, Mary Jo', 'Department of Chemistry and Chemical Biology and Institute for Complex Scientific Software, Northeastern University, Boston, Massachusetts 02115, USA. wei.y@neu.edu <wei.y@neu.edu>|Department of Chemistry and Chemical Biology and Institute for Complex Scientific Software, Northeastern University, Boston, Massachusetts 02115, USA. wei.y@neu.edu <wei.y@neu.edu>|Department of Chemistry and Chemical Biology and Institute for Complex Scientific Software, Northeastern University, Boston, Massachusetts 02115, USA. wei.y@neu.edu <wei.y@neu.edu>|Department of Chemistry and Chemical Biology and Institute for Complex Scientific Software, Northeastern University, Boston, Massachusetts 02115, USA. wei.y@neu.edu <wei.y@neu.edu>', 'United States|United States|United States|United States', 0, 'Binding Sites|Databases, Factual|Models, Chemical|Predictive Value of Tests|Protein Structure, Secondary|Proteins|Software', 'Comparative Study', '10.1186/1471-2105-8-119', '17419878', 'Methods are now available for the prediction of interaction sites in protein 3D structures. While many of these methods report high success rates for site prediction, often these predictions are not very selective and have low precision. Precision in site prediction is addressed using Theoretical Microscopic Titration Curves (THEMATICS), a simple computational method for the identification of active sites in enzymes. Recall and precision are measured and compared with other methods for the prediction of catalytic sites.'),
(91410, 2007, 'bmc', 'BranchClust: a phylogenetic algorithm for selecting gene families', 'Poptsova, Maria S|Gogarten, J Peter', 'Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269-3125, USA. maria.poptsova@uconn.edu|Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269-3125, USA. maria.poptsova@uconn.edu', 'United States|United States', 35, 'Algorithms|Base Sequence|Cluster Analysis|Conserved Sequence|Evolution, Molecular|Molecular Sequence Data|Multigene Family|Phylogeny|Proteome|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-8-120', '17425803', 'Automated methods for assembling families of orthologous genes include those based on sequence similarity scores and those based on phylogenetic approaches. The first are easy to automate but usually they do not distinguish between paralogs and orthologs or have restriction on the number of taxa. Phylogenetic methods often are based on reconciliation of a gene tree with a known rooted species tree, a limitation of this approach, especially in case of prokaryotes, is that the species tree is often unknown, and that from the analyses of single gene families the branching order between related organisms frequently is unresolved.'),
(91411, 2007, 'bmc', 'A network perspective on the topological importance of enzymes and their phylogenetic conservation', 'Liu, Wei-chung|Lin, Wen-hsien|Davis, Andrew J|Jordán, Ferenc|Yang, Hsih-te|Hwang, Ming-jing', 'Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan. wliu56@gate.sinica.edu.tw', '-|-|-|-|-|-', 30, 'Computer Simulation|Enzymes|Evolution, Molecular|Models, Biological|Phylogeny|Signal Transduction|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-121', '17425808', 'A metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node, closeness centrality, which measures how close a node is to others, and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes.'),
(91412, 2007, 'bmc', 'RepSeq--a database of amino acid repeats present in lower eukaryotic pathogens', 'Depledge, Daniel P|Lower, Ryan P J|Smith, Deborah F', 'Immunology and Infection Unit, Department of Biology, University of York, Heslington, York, UK. dd505@york.ac.uk|Immunology and Infection Unit, Department of Biology, University of York, Heslington, York, UK. dd505@york.ac.uk|Immunology and Infection Unit, Department of Biology, University of York, Heslington, York, UK. dd505@york.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 25, 'Animals|Databases, Protein|Eukaryota|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteome|Protozoan Proteins|Repetitive Sequences, Amino Acid|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-122', '17428323', 'Amino acid repeat-containing proteins have a broad range of functions and their identification is of relevance to many experimental biologists. In human-infective protozoan parasites (such as the Kinetoplastid and Plasmodium species), they are implicated in immune evasion and have been shown to influence virulence and pathogenicity. RepSeq http://repseq.gugbe.com is a new database of amino acid repeat-containing proteins found in lower eukaryotic pathogens. The RepSeq database is accessed via a web-based application which also provides links to related online tools and databases for further analyses.'),
(91413, 2007, 'bmc', 'Flexible mapping of homology onto structure with homolmapper', 'Rockwell, Nathan C|Lagarias, J Clark', 'Section of Molecular and Cellular Biology, University of California, Davis, California 95616, USA. ncrockwell@ucdavis.edu|Section of Molecular and Cellular Biology, University of California, Davis, California 95616, USA. ncrockwell@ucdavis.edu', 'United States|United States', 16, 'Computer Graphics|Information Storage and Retrieval|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-123', '17428344', 'Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.'),
(91414, 2006, 'bmc', 'Proceedings of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06), Hangzhou, China, June 20-24, 2006', '-', '-', '-', 16, 'Computational Biology', 'Congress', '10.1186/1471-2105-8-123', '17429870', '-'),
(91415, 2006, 'bmc', 'Proceedings of APBioNet - Fifth International Conference on Bioinformatics (InCoB2006), New Dehli, India, 18-20 December 2006', '-', '-', '-', 16, 'Computational Biology', 'Congress', '10.1186/1471-2105-8-123', '17429871', '-'),
(91416, 2007, 'bmc', 'Significance analysis of microarray transcript levels in time series experiments', 'Di Camillo, Barbara|Toffolo, Gianna|Nair, Sreekumaran K|Greenlund, Laura J|Cobelli, Claudio', 'Information Engineering Department, University of Padova, 35131 Padova, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, 35131 Padova, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, 35131 Padova, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, 35131 Padova, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, 35131 Padova, Italy. dicamill@dei.unipd.it', 'Italy|Italy|Italy|Italy|Italy', 24, 'Algorithms|Artifacts|Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Research|Sample Size|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S10', '17430554', 'Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over time, a first necessary step is to select differentially expressed transcripts. A variety of methods have been proposed to this purpose, however, these methods are seldom applicable in practice since they require a large number of replicates, often available only for a limited number of samples. In this data-poor context, we evaluate the performance of three selection methods, using synthetic data, over a range of experimental conditions. Application to real data is also discussed.'),
(91417, 2007, 'bmc', 'ProCMD: a database and 3D web resource for protein C mutants', 'DUrsi, Pasqualina|Marino, Francesca|Caprera, Andrea|Milanesi, Luciano|Faioni, Elena M|Rovida, Ermanna', 'Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it|Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it|Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it|Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it|Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it|Department of Science and Biomedical Technologies, University of Milano, Italy. pasqualina.dursi@itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 24, 'Amino Acid Sequence|Computer Graphics|Database Management Systems|Databases, Protein|Imaging, Three-Dimensional|Information Storage and Retrieval|Internet|Molecular Sequence Data|Mutation|Protein C|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S1-S11', '17430555', 'Activated Protein C (ProC) is an anticoagulant plasma serine protease which also plays an important role in controlling inflammation and cell proliferation. Several mutations of the gene are associated with phenotypic functional deficiency of protein C, and with the risk of developing venous thrombosis. Structure prediction and computational analysis of the mutants have proven to be a valuable aid in understanding the molecular aspects of clinical thrombophilia.'),
(91418, 2007, 'bmc', 'On the origin and evolution of biosynthetic pathways: integrating microarray data with structure and organization of the Common Pathway genes', 'Fondi, Marco|Brilli, Matteo|Fani, Renato', 'Dipartimento di Biologia Animale e Genetica, Università di Firenze, Via Romana 1719, Firenze, Italy. marco.fondi@unifi.it|Dipartimento di Biologia Animale e Genetica, Università di Firenze, Via Romana 1719, Firenze, Italy. marco.fondi@unifi.it|Dipartimento di Biologia Animale e Genetica, Università di Firenze, Via Romana 1719, Firenze, Italy. marco.fondi@unifi.it', 'Italy|Italy|Italy', 12, 'Bacterial Proteins|Computer Simulation|Evolution, Molecular|Models, Genetic|Multienzyme Complexes|Proteobacteria|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-S1-S12', '17430556', 'The lysine, threonine, and methionine biosynthetic pathways share the three initial enzymatic steps, which are referred to as the Common Pathway (CP). In Escherichia coli three different aspartokinases (AKI, AKII, AKIII, the products of thrA, metL and lysC, respectively) can perform the first step of the CP. Moreover, two of them (AKI and AKII) are bifunctional, carrying also homoserine dehydrogenasic activity (hom product). The second step of the CP is catalyzed by a single aspartate semialdehyde dehydrogenase (ASDH, the product of asd). Thus, in the CP of E. coli while a single copy of ASDH performs the same reaction for three different metabolic routes, three different AKs perfom a unique step. Why and how such a situation did emerge and maintain? How is it correlated to the different regulatory mechanisms acting on these genes? The aim of this work was to trace the evolutionary pathway leading to the extant scenario in proteobacteria.'),
(91419, 2007, 'bmc', 'ESTuber db: an online database for Tuber borchii EST sequences', 'Lazzari, Barbara|Caprera, Andrea|Cosentino, Cristian|Stella, Alessandra|Milanesi, Luciano|Viotti, Angelo', 'Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it|Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it|Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it|Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it|Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it|Istituto di Biologia e Biotecnologia Agraria, via Bassini 15, 20133 Milan, Italy. lazzari@ibba.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 9, 'Ascomycota|Chromosome Mapping|DNA, Fungal|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Online Systems|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S1-S13', '17430557', 'The ESTuber database (http://www.itb.cnr.it/estuber) includes 3,271 Tuber borchii expressed sequence tags (EST). The dataset consists of 2,389 sequences from an in-house prepared cDNA library from truffle vegetative hyphae, and 882 sequences downloaded from GenBank and representing four libraries from white truffle mycelia and ascocarps at different developmental stages. An automated pipeline was prepared to process EST sequences using public software integrated by in-house developed Perl scripts. Data were collected in a MySQL database, which can be queried via a php-based web interface.'),
(91420, 2007, 'bmc', 'Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists', 'Masseroli, Marco|Bellistri, Elisa|Franceschini, Andrea|Pinciroli, Francesco', 'Dipartimento di Elettronica e Informazione, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy. masseroli@elet.polimi.it|Dipartimento di Elettronica e Informazione, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy. masseroli@elet.polimi.it|Dipartimento di Elettronica e Informazione, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy. masseroli@elet.polimi.it|Dipartimento di Elettronica e Informazione, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy. masseroli@elet.polimi.it', 'Italy|Italy|Italy|Italy', 1, 'Chromosome Mapping|Cluster Analysis|Data Interpretation, Statistical|Databases, Protein|Information Storage and Retrieval|Multigene Family|Protein Structure, Tertiary|Proteome', 'Journal Article', '10.1186/1471-2105-8-S1-S14', '17430558', 'The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within GFINDer, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining.'),
(91421, 2007, 'bmc', 'Environment specific substitution tables for thermophilic proteins', 'Mizuguchi, K|Sele, M|Cubellis, M V', 'Department of Biochemistry, University of Cambridge, UK. kenji@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, UK. kenji@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, UK. kenji@cryst.bioc.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 31, 'Adaptation, Physiological|Amino Acid Substitution|Archaea|Bacterial Proteins|Chromosome Mapping|Conserved Sequence|Environment|Sequence Alignment|Sequence Analysis, Protein|Temperature', 'Journal Article', '10.1186/1471-2105-8-S1-S15', '17430559', 'Thermophilic organisms are able to live at high temperatures ranging from 50 to > 100 degrees C. Their proteins must be sufficiently stable to function under these extreme conditions, however, the basis for thermostability remains elusive. Subtle differences between thermophilic and mesophilic molecules can be found when sequences or structures from homologous proteins are compared, but often these differences are family-specific and few general rules have been derived. The availability of complete genome sequences has now made it feasible to perform a large-scale comparison between mesophilic and thermophilic proteins, the latter of which primarily come from archaeal genomes although a few complete genomes of thermophilic eubacteria are also available.'),
(91422, 2007, 'bmc', 'Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation', 'Neretti, Nicola|Remondini, Daniel|Tatar, Marc|Sedivy, John M|Pierini, Michela|Mazzatti, Dawn|Powell, Jonathan|Franceschi, Claudio|Castellani, Gastrone C', 'Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu|Institute for Brain and Neural Systems, Brown University, Providence RI, USA. nicola_neretti@brown.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 4, 'Adaptation, Physiological|Computer Simulation|Gene Expression|Gene Expression Regulation|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-8-S1-S16', '17430560', 'Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measures of their expression dynamics. In this paper we apply a correlation based approach to network reconstruction to three datasets of time series gene expression following system perturbation: 1) Conditional, Tamoxifen dependent, activation of the cMyc proto-oncogene in rat fibroblast, 2) Genomic response to nutrition changes in D. melanogaster, 3) Patterns of gene activity as a consequence of ageing occurring over a life-span time series (25y-90y) sampled from T-cells of human donors. We show that the three datasets undergo similar transitions from an uncorrelated regime to a positively or negatively correlated one that is symptomatic of a shift from a ground or basal state to a polarized state. In addition, we show that a similar transition is conserved at the pathway level, and that this information can be used for the construction of meta-networks where it is possible to assess new relations among functionally distant sets of molecular functions.'),
(91423, 2007, 'bmc', 'Splicy: a web-based tool for the prediction of possible alternative splicing events from Affymetrix probeset data', 'Rambaldi, Davide|Felice, Barbara|Praz, Viviane|Bucher, Philip|Cittaro, Davide|Guffanti, Alessandro', 'The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it|The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it|The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it|The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it|The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it|The IFOM-IEO Campus, Via Adamello, 16-20139 Milano, Italy. davide.rambaldi@ifom-ieo-campus.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 7, 'Alternative Splicing|Chromosome Mapping|DNA Probes|Databases, Genetic|Internet|Oligonucleotide Array Sequence Analysis|RNA Splice Sites|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S17', '17430561', 'The Affymetrix technology is nowadays a well-established method for the analysis of gene expression profiles in cancer research studies. However, changes in gene expression levels are not the only way to link genes and disease. The existence of gene isoforms specifically linked with cancer or apoptosis is increasingly found in literature. Hence it is of great interest to associate the results of a gene expression study with updated evidences on the transcript structure and its possible variants.'),
(91424, 2007, 'bmc', 'SYMBIOmatics: synergies in Medical Informatics and Bioinformatics--exploring current scientific literature for emerging topics', 'Rebholz-Schuhman, Dietrich|Cameron, Graham|Clark, Dominic|van Mulligen, Erik|Coatrieux, Jean-Louis|Del Hoyo Barbolla, Eva|Martin-Sanchez, Fernando|Milanesi, Luciano|Porro, Ivan|Beltrame, Francesco|Tollis, Ioannis|Van der Lei, Johan', 'EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 19, 'Biotechnology|Computational Biology|Forecasting|Medical Informatics|Natural Language Processing|Periodicals as Topic|Science|Systems Integration|Technology Assessment, Biomedical', 'Journal Article', '10.1186/1471-2105-8-S1-S18', '17430562', 'The SYMBIOmatics Specific Support Action (SSA) is an information gathering and dissemination activity that seeks to identify synergies between the bioinformatics and the medical informatics domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics.'),
(91425, 2007, 'bmc', 'Biowep: a workflow enactment portal for bioinformatics applications', 'Romano, Paolo|Bartocci, Ezio|Bertolini, Guglielmo|De Paoli, Flavio|Marra, Domenico|Mauri, Giancarlo|Merelli, Emanuela|Milanesi, Luciano', 'Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, Italy. paolo.romano@istge.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 34, 'Algorithms|Computational Biology|Computer Graphics|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S1-S19', '17430563', 'The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91426, 2007, 'bmc', 'BioWMS: a web-based Workflow Management System for bioinformatics', 'Bartocci, Ezio|Corradini, Flavio|Merelli, Emanuela|Scortichini, Lorenzo', 'Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n,9, Camerino, MC, I-62032, Italy. ezio.bartocci@unicam.it|Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n,9, Camerino, MC, I-62032, Italy. ezio.bartocci@unicam.it|Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n,9, Camerino, MC, I-62032, Italy. ezio.bartocci@unicam.it|Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n,9, Camerino, MC, I-62032, Italy. ezio.bartocci@unicam.it', 'Italy|Italy|Italy|Italy', 38, 'Computational Biology|Computer Graphics|Database Management Systems|Information Storage and Retrieval|Internet|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S1-S2', '17430564', 'An in-silico experiment can be naturally specified as a workflow of activities implementing, in a standardized environment, the process of data and control analysis. A workflow has the advantage to be reproducible, traceable and compositional by reusing other workflows. In order to support the daily work of a bioscientist, several Workflow Management Systems (WMSs) have been proposed in bioinformatics. Generally, these systems centralize the workflow enactment and do not exploit standard process definition languages to describe, in order to be reusable, workflows. While almost all WMSs require heavy stand-alone applications to specify new workflows, only few of them provide a web-based process definition tool.'),
(91427, 2007, 'bmc', 'p53FamTaG: a database resource of human p53, p63 and p73 direct target genes combining in silico prediction and microarray data', 'Sbisà, Elisabetta|Catalano, Domenico|Grillo, Giorgio|Licciulli, Flavio|Turi, Antonio|Liuni, Sabino|Pesole, Graziano|De Grassi, Anna|Caratozzolo, Mariano Francesco|DErchia, Anna Maria|Navarro, Beatriz|Tullo, Apollonia|Saccone, Cecilia|Gisel, Andreas', 'Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it|Istituto di Tecnologie Biomediche-Sede di Bari, CNR, Via Amendola, 122/D 70126 Bari, Italy. elisabetta.sbisa@ba.itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Binding Sites|DNA-Binding Proteins|Databases, Genetic|Gene Targeting|Humans|Multigene Family|Nuclear Proteins|Oligonucleotide Array Sequence Analysis|Protein Binding|Protein Interaction Mapping|Software|Trans-Activators|Transcription Factors|Tumor Suppressor Protein p53|Tumor Suppressor Proteins', 'Journal Article', '10.1186/1471-2105-8-S1-S20', '17430565', 'The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis and repair, growth arrest, apoptosis, genome stability, angiogenesis, development and differentiation. These genes encode sequence-specific nuclear transcription factors that recognise the same responsive element (RE) in their target genes. Their inactivation or aberrant expression may determine tumour progression or developmental disease. The discovery of several protein isoforms with antagonistic roles, which are produced by the expression of different promoters and alternative splicing, widened the complexity of the scenario of the transcriptional network of the p53 family members. Therefore, the identification of the genes transactivated by p53 family members is crucial to understand the specific role for each gene in cell cycle regulation. We have combined a genome-wide computational search of p53 family REs and microarray analysis to identify new direct target genes. The huge amount of biological data produced has generated a critical need for bioinformatic tools able to manage and integrate such data and facilitate their retrieval and analysis.'),
(91428, 2007, 'bmc', 'The genopolis microarray database', 'Splendiani, Andrea|Brandizi, Marco|Even, Gael|Beretta, Ottavio|Pavelka, Norman|Pelizzola, Mattia|Mayhaus, Manuel|Foti, Maria|Mauri, Giancarlo|Ricciardi-Castagnoli, Paola', 'Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it|Department Informatics, Systemistics and Communication, University of Milano-Bicocca, Via degli Arcimboldi 8, Milano, Italy. andrea.splendiani@unimib.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S21', '17430566', 'Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood. Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions.'),
(91429, 2007, 'bmc', 'Data handling strategies for high throughput pyrosequencers', 'Trombetti, Gabriele A|Bonnal, Raoul J P|Rizzi, Ermanno|De Bellis, Gianluca|Milanesi, Luciano', 'Institute for Biomedical Technologies-National Research Council, via Fratelli Cervi 93, 20090 Segrate, MI, Italy. gabriele.trombetti@itb.cnr.it|Institute for Biomedical Technologies-National Research Council, via Fratelli Cervi 93, 20090 Segrate, MI, Italy. gabriele.trombetti@itb.cnr.it|Institute for Biomedical Technologies-National Research Council, via Fratelli Cervi 93, 20090 Segrate, MI, Italy. gabriele.trombetti@itb.cnr.it|Institute for Biomedical Technologies-National Research Council, via Fratelli Cervi 93, 20090 Segrate, MI, Italy. gabriele.trombetti@itb.cnr.it|Institute for Biomedical Technologies-National Research Council, via Fratelli Cervi 93, 20090 Segrate, MI, Italy. gabriele.trombetti@itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy', 21, 'Algorithms|DNA|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S22', '17430567', 'New high throughput pyrosequencers such as the 454 Life Sciences GS 20 are capable of massively parallelizing DNA sequencing providing an unprecedented rate of output data as well as potentially reducing costs. However, these new pyrosequencers bear a different error profile and provide shorter reads than those of a more traditional Sanger sequencer. These facts pose new challenges regarding how the data are handled and analyzed, in addition, the steep increase in the sequencers throughput calls for much computation power at a low cost.'),
(91430, 2007, 'bmc', 'A global gene evolution analysis on Vibrionaceae family using phylogenetic profile', 'Vitulo, Nicola|Vezzi, Alessandro|Romualdi, Chiara|Campanaro, Stefano|Valle, Giorgio', 'CRIBI Biotechnology Centre, Department of Biology, University of Padova, Padova, Italy. nicolav@cribi.unipd.it|CRIBI Biotechnology Centre, Department of Biology, University of Padova, Padova, Italy. nicolav@cribi.unipd.it|CRIBI Biotechnology Centre, Department of Biology, University of Padova, Padova, Italy. nicolav@cribi.unipd.it|CRIBI Biotechnology Centre, Department of Biology, University of Padova, Padova, Italy. nicolav@cribi.unipd.it|CRIBI Biotechnology Centre, Department of Biology, University of Padova, Padova, Italy. nicolav@cribi.unipd.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Biological Evolution|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Genetic Variation|Genome, Bacterial|Phylogeny|Species Specificity|Vibrionaceae', 'Journal Article', '10.1186/1471-2105-8-S1-S23', '17430568', 'Vibrionaceae represent a significant portion of the cultivable heterotrophic sea bacteria, they strongly affect nutrient cycling and some species are devastating pathogens. In this work we propose an improved phylogenetic profile analysis on 14 Vibrionaceae genomes, to study the evolution of this family on the basis of gene content. The phylogenetic profile is based on the observation that genes involved in the same process (e.g. metabolic pathway or structural complex) tend to be concurrently present or absent within different genomes. This allows the prediction of hypothetical functions on the basis of a shared phylogenetic profiles. Moreover this approach is useful to identify putative laterally transferred elements on the basis of their presence on distantly phylogenetically related bacteria.'),
(91431, 2007, 'bmc', 'Local comparison of protein structures highlights cases of convergent evolution in analogous functional sites', 'Ausiello, Gabriele|Peluso, Daniele|Via, Allegra|Helmer-Citterich, Manuela', 'Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Rome, Italy. gabriele.ausiello@uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Rome, Italy. gabriele.ausiello@uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Rome, Italy. gabriele.ausiello@uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Rome, Italy. gabriele.ausiello@uniroma2.it', 'Italy|Italy|Italy|Italy', 14, 'Amino Acid Sequence|Binding Sites|Conserved Sequence|Evolution, Molecular|Molecular Sequence Data|Protein Binding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-8-S1-S24', '17430569', 'We performed an exhaustive search for local structural similarities in an ensemble of non-redundant protein functional sites. With the purpose of finding new examples of convergent evolution, we selected only those matching sites composed of structural regions whose residue order is inverted in the relative protein sequences.'),
(91432, 2007, 'bmc', 'A computational approach for detecting peptidases and their specific inhibitors at the genome level', 'Bartoli, Lisa|Calabrese, Remo|Fariselli, Piero|Mita, Damiano G|Casadio, Rita', 'Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy. lisa@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy. lisa@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy. lisa@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy. lisa@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy. lisa@biocomp.unibo.it', 'Italy|Italy|Italy|Italy|Italy', 3, 'Algorithms|Amino Acid Sequence|Binding Sites|Genomics|Molecular Sequence Data|Peptide Hydrolases|Protease Inhibitors|Protein Binding|Proteome|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-S1-S3', '17430570', 'Peptidases are proteolytic enzymes responsible for fundamental cellular activities in all organisms. Apparently about 2-5% of the genes encode for peptidases, irrespectively of the organism source. The basic peptidase function is protein digestion and this can be potentially dangerous in living organisms when it is not strictly controlled by specific inhibitors. In genome annotation a basic question is to predict gene function. Here we describe a computational approach that can filter peptidases and their inhibitors out of a given proteome. Furthermore and as an added value to MEROPS, a specific database for peptidases already available in the public domain, our method can predict whether a pair of peptidase/inhibitor can interact, eventually listing all possible predicted ligands (peptidases and/or inhibitors).'),
(91433, 2007, 'bmc', 'ProtNet: a tool for stochastic simulations of protein interaction networks dynamics', 'Bernaschi, Massimo|Castiglione, Filippo|Ferranti, Alessandra|Gavrila, Caius|Tinti, Michele|Cesareni, Gianni', 'Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it|Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it|Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it|Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it|Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it|Istituto per le Applicazioni del Calcolo M. Picone, CNR, V,le del Policlinico 137, Rome, Italy. massimo@iac.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 8, 'Computer Simulation|Data Interpretation, Statistical|Kinetics|Models, Biological|Models, Statistical|Protein Interaction Mapping|Proteome|Signal Transduction|Software|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-8-S1-S4', '17430571', 'Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim at describing the cell interactome. These data are usually presented as graphs where proteins (nodes) are linked by edges to their experimentally determined partners. This representation reveals that protein-protein interaction (PPI) networks, like other kinds of complex networks, are not randomly organized and display properties that are typical of hierarchical networks, combining modularity and local clustering to scale free topology. However informative, this representation is static and provides no clue about the dynamic nature of protein interactions inside the cell.'),
(91434, 2007, 'bmc', 'Cross platform microarray analysis for robust identification of differentially expressed genes', 'Bosotti, Roberta|Locatelli, Giuseppe|Healy, Sandra|Scacheri, Emanuela|Sartori, Luca|Mercurio, Ciro|Calogero, Raffaele|Isacchi, Antonella', 'Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com|Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Biomarkers, Tumor|Cell Line, Tumor|Data Interpretation, Statistical|Female|Gene Expression Profiling|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-8-S1-S5', '17430572', 'Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles. In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.'),
(91435, 2007, 'bmc', 'The MEPS server for identifying protein conformational epitopes', 'Castrignanò, Tiziana|De Meo, Paolo DOnorio|Carrabino, Danilo|Orsini, Massimilano|Floris, Matteo|Tramontano, Anna', 'CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it|CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it|CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it|CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it|CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it|CASPUR, Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita e Ricerca, Via dei Tizii, 6/b, 5 I-00185 Rome, Italy. Tiziana.Castrignano@caspur.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Antibodies|Computational Biology|Epitope Mapping|Internet|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S6', '17430573', 'One of the most interesting problems in molecular immunology is epitope mapping, i.e. the identification of the regions of interaction between an antigen and an antibody. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues involved in the interaction and could be instrumental both in designing peptides able to mimic the interacting surface of the antigen and in understanding where immunologically important regions are located in its three-dimensional structure. From an experimental point of view, both genetically encoded and chemically synthesised peptide libraries can be used to identify sequences recognized by a given antibody. The problem then arises of which region of a folded protein the selected peptides correspond to.'),
(91436, 2007, 'bmc', 'A Grid-based solution for management and analysis of microarrays in distributed experiments', 'Porro, Ivan|Torterolo, Livia|Corradi, Luca|Fato, Marco|Papadimitropoulos, Adam|Scaglione, Silvia|Schenone, Andrea|Viti, Federica', 'Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it|Computer Science, Systems, and Communication Department, University of Genova, Viale Causa 12, 16100 Genova, Italy. pivan@dist.unige.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 10, 'Algorithms|Computer Simulation|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Models, Biological|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-8-S1-S7', '17430574', 'Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of uploading and accessing distributed datasets through the Grid middleware and against its ability in managing the execution of jobs on distributed computational resources. Results from the Grid test will be discussed in a further paper.'),
(91437, 2007, 'bmc', 'The BioPrompt-box: an ontology-based clustering tool for searching in biological databases', 'Corsi, Claudio|Ferragina, Paolo|Marangoni, Roberto', 'Dipartimento di Informatica, University of Pisa, Italy. claudio.corsi@gmail.com|Dipartimento di Informatica, University of Pisa, Italy. claudio.corsi@gmail.com|Dipartimento di Informatica, University of Pisa, Italy. claudio.corsi@gmail.com', 'Italy|Italy|Italy', 0, 'Algorithms|Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Publications|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S1-S8', '17430575', 'High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and understanding becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective.'),
(91438, 2007, 'bmc', 'Gene models from ESTs (GeneModelEST): an application on the Solanum lycopersicum genome', 'DAgostino, Nunzio|Traini, Alessandra|Frusciante, Luigi|Chiusano, Maria Luisa', 'Department of Structural and Functional Biology, University Federico II, 80126 Naples, Italy. nunzio.dagostino@gmail.com|Department of Structural and Functional Biology, University Federico II, 80126 Naples, Italy. nunzio.dagostino@gmail.com|Department of Structural and Functional Biology, University Federico II, 80126 Naples, Italy. nunzio.dagostino@gmail.com|Department of Structural and Functional Biology, University Federico II, 80126 Naples, Italy. nunzio.dagostino@gmail.com', 'Italy|Italy|Italy|Italy', 0, 'Algorithms|Chromosome Mapping|Expressed Sequence Tags|Genome, Plant|Lycopersicon esculentum|Models, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-S1-S9', '17430576', 'The structure annotation of a genome is based either on ab initio methodologies or on similaritiy searches versus molecules that have been already annotated. Ab initio gene predictions in a genome are based on a priori knowledge of species-specific features of genes. The training of ab initio gene finders is based on the definition of a data-set of gene models. To accomplish this task the common approach is to align species-specific full length cDNA and EST sequences along the genomic sequences in order to define exon/intron structure of mRNA coding genes.'),
(91439, 2007, 'bmc', 'A full Bayesian hierarchical mixture model for the variance of gene differential expression', 'Manda, Samuel O M|Walls, Rebecca E|Gilthorpe, Mark S', 'Biostatistics Unit, Centre for Epidemiology and Biostatistics, Leeds, UK. s.o.m.manda@leeds.ac.uk|Biostatistics Unit, Centre for Epidemiology and Biostatistics, Leeds, UK. s.o.m.manda@leeds.ac.uk|Biostatistics Unit, Centre for Epidemiology and Biostatistics, Leeds, UK. s.o.m.manda@leeds.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 6, 'Bayes Theorem|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-124', '17439644', 'In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccurate. Visual inspection of graphical summaries of these data usually reveals that heteroscedasticity is present, and the standard approach to address this is to take a log2 transformation. In such circumstances, it is then common to assume that gene variability is constant when an analysis of these data is undertaken. However, this is perhaps too stringent an assumption. More careful inspection reveals that the simple log2 transformation does not remove the problem of heteroscedasticity. An alternative strategy is to assume independent gene-specific variances, although again this is problematic as variance estimates based on few replications are highly unstable. More meaningful and reliable comparisons of gene expression might be achieved, for different conditions or different tissue samples, where the test statistics are based on accurate estimates of gene variability, a crucial step in the identification of differentially expressed genes.'),
(91440, 2007, 'bmc', 'Detecting microsatellites within genomes: significant variation among algorithms', 'Leclercq, Sébastien|Rivals, Eric|Jarne, Philippe', 'LIRMM, UMR 5506 CNRS--Université de Montpellier II, Montpellier, France. sebastien.leclercq@cefe.cnrs.fr|LIRMM, UMR 5506 CNRS--Université de Montpellier II, Montpellier, France. sebastien.leclercq@cefe.cnrs.fr|LIRMM, UMR 5506 CNRS--Université de Montpellier II, Montpellier, France. sebastien.leclercq@cefe.cnrs.fr', 'France|France|France', 0, 'Algorithms|Animals|Chromosomes, Human, X|Drosophila melanogaster|Female|Genome|Humans|Microsatellite Repeats|Neurospora crassa|Reproducibility of Results|Saccharomyces cerevisiae|Sequence Analysis, DNA|Species Specificity|X Chromosome', 'Comparative Study', '10.1186/1471-2105-8-125', '17442102', 'Microsatellites are short, tandemly-repeated DNA sequences which are widely distributed among genomes. Their structure, role and evolution can be analyzed based on exhaustive extraction from sequenced genomes. Several dedicated algorithms have been developed for this purpose. Here, we compared the detection efficiency of five of them (TRF, Mreps, Sputnik, STAR, and RepeatMasker).'),
(91441, 2007, 'bmc', 'UbiProt: a database of ubiquitylated proteins', 'Chernorudskiy, Alexander L|Garcia, Alejandro|Eremin, Eugene V|Shorina, Anastasia S|Kondratieva, Ekaterina V|Gainullin, Murat R', 'Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>|Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>|Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>|Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>|Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>|Nizhny Novgorod State University, Nizhny Novgorod, Russia. chalbio@mail.ru <chalbio@mail.ru>', '-|-|-|-|-|-', 51, 'Amino Acid Sequence|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Ubiquitin|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-126', '17442109', 'Post-translational protein modification with ubiquitin, or ubiquitylation, is one of the hottest topics in a modern biology due to a dramatic impact on diverse metabolic pathways and involvement in pathogenesis of severe human diseases. A great number of eukaryotic proteins was found to be ubiquitylated. However, data about particular ubiquitylated proteins are rather disembodied.'),
(91442, 2007, 'bmc', 'Algebraic correction methods for computational assessment of clone overlaps in DNA fingerprint mapping', 'Wendl, Michael C', 'Genome Sequencing Center, Washington University, St. Louis, MO 63108, USA. mwendl@wustl.edu', 'United States', 3, 'Algorithms|Artifacts|Chromosome Mapping|Computer Simulation|DNA Fingerprinting|Data Interpretation, Statistical|Models, Genetic|Models, Statistical|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-127', '17442113', 'The Sulston score is a well-established, though approximate metric for probabilistically evaluating postulated clone overlaps in DNA fingerprint mapping. It is known to systematically over-predict match probabilities by various orders of magnitude, depending upon project-specific parameters. Although the exact probability distribution is also available for the comparison problem, it is rather difficult to compute and cannot be used directly in most cases. A methodology providing both improved accuracy and computational economy is required.'),
(91443, 2007, 'bmc', 'TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays', 'Kim, Chulyun|Kim, Sangkyum|Dorer, Russell|Xie, Dan|Han, Jiawei|Zhong, Sheng', 'Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>|Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>|Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>|Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>|Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>|Department Computer Science, University of Illinois at Urbana Champaign, Urbana, IL, USA. ckim5@uiuc.edu <ckim5@uiuc.edu>', 'United States|United States|United States|United States|United States|United States', 0, 'Internet|Mutation|Protein Array Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1186/1471-2105-8-128', '17442117', 'A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames) of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages.'),
(91444, 2007, 'bmc', 'CGKB: an annotation knowledge base for cowpea (Vigna unguiculata L) methylation filtered genomic genespace sequences', 'Chen, Xianfeng|Laudeman, Thomas W|Rushton, Paul J|Spraggins, Thomas A|Timko, Michael P', 'Department of Microbiology, University of Virginia Health System, Charlottesville, VA 29908, USA. xc3m@virginia.edu <xc3m@virginia.edu>|Department of Microbiology, University of Virginia Health System, Charlottesville, VA 29908, USA. xc3m@virginia.edu <xc3m@virginia.edu>|Department of Microbiology, University of Virginia Health System, Charlottesville, VA 29908, USA. xc3m@virginia.edu <xc3m@virginia.edu>|Department of Microbiology, University of Virginia Health System, Charlottesville, VA 29908, USA. xc3m@virginia.edu <xc3m@virginia.edu>|Department of Microbiology, University of Virginia Health System, Charlottesville, VA 29908, USA. xc3m@virginia.edu <xc3m@virginia.edu>', 'United States|United States|United States|United States|United States', 40, 'Chromosome Mapping|DNA Methylation|Database Management Systems|Databases, Genetic|Fabaceae|Genetic Markers|Genome, Plant|Information Storage and Retrieval|Internet|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-129', '17445272', 'Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important food and forage legumes in the semi-arid tropics because of its ability to tolerate drought and grow on poor soils. It is cultivated mostly by poor farmers in developing countries, with 80% of production taking place in the dry savannah of tropical West and Central Africa. Cowpea is largely an underexploited crop with relatively little genomic information available for use in applied plant breeding. The goal of the Cowpea Genomics Initiative (CGI), funded by the Kirkhouse Trust, a UK-based charitable organization, is to leverage modern molecular genetic tools for gene discovery and cowpea improvement. One aspect of the initiative is the sequencing of the gene-rich region of the cowpea genome (termed the genespace) recovered using methylation filtration technology and providing annotation and analysis of the sequence data.'),
(91445, 2007, 'bmc', 'Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign', 'Harmanci, Arif Ozgun|Sharma, Gaurav|Mathews, David H', 'Department of Electrical and Computer Engineering, University of Rochester, Hopeman 204, Rochester, NY 14627, USA. arharman@ece.rochester.edu <arharman@ece.rochester.edu>|Department of Electrical and Computer Engineering, University of Rochester, Hopeman 204, Rochester, NY 14627, USA. arharman@ece.rochester.edu <arharman@ece.rochester.edu>|Department of Electrical and Computer Engineering, University of Rochester, Hopeman 204, Rochester, NY 14627, USA. arharman@ece.rochester.edu <arharman@ece.rochester.edu>', 'United States|United States|United States', 0, 'Models, Statistical|Predictive Value of Tests|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1186/1471-2105-8-130', '17445273', 'Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction.'),
(91446, 2007, 'bmc', 'Statistical significance of quantitative PCR', 'Karlen, Yann|McNair, Alan|Perseguers, Sébastien|Mazza, Christian|Mermod, Nicolas', 'Institute of Biotechnology, University of Lausanne, Lausanne, Switzerland. yann.karlen@tele2.ch <yann.karlen@tele2.ch>|Institute of Biotechnology, University of Lausanne, Lausanne, Switzerland. yann.karlen@tele2.ch <yann.karlen@tele2.ch>|Institute of Biotechnology, University of Lausanne, Lausanne, Switzerland. yann.karlen@tele2.ch <yann.karlen@tele2.ch>|Institute of Biotechnology, University of Lausanne, Lausanne, Switzerland. yann.karlen@tele2.ch <yann.karlen@tele2.ch>|Institute of Biotechnology, University of Lausanne, Lausanne, Switzerland. yann.karlen@tele2.ch <yann.karlen@tele2.ch>', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 222, 'Base Sequence|Gene Expression Regulation|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-131', '17445280', 'PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness.'),
(91447, 2007, 'bmc', 'A verification protocol for the probe sequences of Affymetrix genome arrays reveals high probe accuracy for studies in mouse, human and rat', 'Alberts, Rudi|Terpstra, Peter|Hardonk, Menno|Bystrykh, Leonid V|de Haan, Gerald|Breitling, Rainer|Nap, Jan-Peter|Jansen, Ritsert C', 'Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands. r.alberts@rug.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 11, 'Animals|Base Sequence|Chromosome Mapping|DNA Probes|Databases, Genetic|Humans|Mice|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Rats|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-8-132', '17448222', 'The Affymetrix GeneChip technology uses multiple probes per gene to measure its expression level. Individual probe signals can vary widely, which hampers proper interpretation. This variation can be caused by probes that do not properly match their target gene or that match multiple genes. To determine the accuracy of Affymetrix arrays, we developed an extensive verification protocol, for mouse arrays incorporating the NCBI RefSeq, NCBI UniGene Unique, NIA Mouse Gene Index, and UCSC mouse genome databases.'),
(91448, 2007, 'bmc', 'A mass accuracy sensitive probability based scoring algorithm for database searching of tandem mass spectrometry data', 'Xu, Hua|Freitas, Michael A', 'Department of Chemistry, the Ohio State University, Columbus 43210, OH, USA. xu.171@osu.edu <xu.171@osu.edu>|Department of Chemistry, the Ohio State University, Columbus 43210, OH, USA. xu.171@osu.edu <xu.171@osu.edu>', 'United States|United States', 0, 'Algorithms|Data Interpretation, Statistical|Databases, Genetic|Information Storage and Retrieval|Probability|Proteomics|Sensitivity and Specificity|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-8-133', '17448237', 'Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become one of the most used tools in mass spectrometry based proteomics. Various algorithms have since been developed to automate the process for modern high-throughput LC-MS/MS experiments.'),
(91449, 2007, 'bmc', 'Spatial location and its relevance for terminological inferences in bio-ontologies', 'Schulz, Stefan|Markó, Kornél|Hahn, Udo', 'Medical Informatics Department, Freiburg University Hospital, Freiburg, Germany. stschulz@uni-freiburg.de|Medical Informatics Department, Freiburg University Hospital, Freiburg, Germany. stschulz@uni-freiburg.de|Medical Informatics Department, Freiburg University Hospital, Freiburg, Germany. stschulz@uni-freiburg.de', 'Germany|Germany|Germany', 8, 'Classification|Computational Biology|Databases, Factual|Information Storage and Retrieval|Logic|Models, Theoretical|Semantics', 'Journal Article', '10.1186/1471-2105-8-134', '17448242', 'An adequate and expressive ontological representation of biological organisms and their parts requires formal reasoning mechanisms for their relations of physical aggregation and containment.'),
(91450, 2007, 'bmc', 'Supervised multivariate analysis of sequence groups to identify specificity determining residues', 'Wallace, Iain M|Higgins, Desmond G', 'The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland. iain.wallace@ucd.ie|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland. iain.wallace@ucd.ie', 'Ireland|Ireland', 19, 'Amino Acid Sequence|Base Sequence|Multivariate Analysis|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-135', '17451607', 'Proteins that evolve from a common ancestor can change functionality over time, and it is important to be able identify residues that cause this change. In this paper we show how a supervised multivariate statistical method, Between Group Analysis (BGA), can be used to identify these residues from families of proteins with different substrate specifities using multiple sequence alignments.'),
(91451, 2007, 'bmc', 'An adaptive bin framework search method for a beta-sheet protein homopolymer model', 'Shmygelska, Alena|Hoos, Holger H', 'Department of Structural Biology, Stanford University, Stanford, CA 94305, USA. alenas@stanford.edu|Department of Structural Biology, Stanford University, Stanford, CA 94305, USA. alenas@stanford.edu', 'United States|United States', 0, 'Amino Acid Sequence|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-136', '17451609', 'The problem of protein structure prediction consists of predicting the functional or native structure of a protein given its linear sequence of amino acids. This problem has played a prominent role in the fields of biomolecular physics and algorithm design for over 50 years. Additionally, its importance increases continually as a result of an exponential growth over time in the number of known protein sequences in contrast to a linear increase in the number of determined structures. Our work focuses on the problem of searching an exponentially large space of possible conformations as efficiently as possible, with the goal of finding a global optimum with respect to a given energy function. This problem plays an important role in the analysis of systems with complex search landscapes, and particularly in the context of ab initio protein structure prediction.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91452, 2007, 'bmc', 'Spectral estimation in unevenly sampled space of periodically expressed microarray time series data', 'Liew, Alan Wee-Chung|Xian, Jun|Wu, Shuanhu|Smith, David|Yan, Hong', 'School of Information & Communication Technology, Griffith University, Brisbane, Australia. a.liew@griffith.edu.au|School of Information & Communication Technology, Griffith University, Brisbane, Australia. a.liew@griffith.edu.au|School of Information & Communication Technology, Griffith University, Brisbane, Australia. a.liew@griffith.edu.au|School of Information & Communication Technology, Griffith University, Brisbane, Australia. a.liew@griffith.edu.au|School of Information & Communication Technology, Griffith University, Brisbane, Australia. a.liew@griffith.edu.au', 'Australia|Australia|Australia|Australia|Australia', 25, 'Algorithms|Animals|Fourier Analysis|Gene Expression|Gene Expression Profiling|Genes, Fungal|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Periodicity|Plasmodium falciparum|Signal Processing, Computer-Assisted', 'Comparative Study', '10.1186/1471-2105-8-137', '17451610', 'Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically expressed. Such challenge occurs due to the fact that the observed time series usually exhibit non-idealities, such as noise, short length, and unevenly sampled time points. Most methods used in the literature operate on evenly sampled time series and are not suitable for unevenly sampled time series.'),
(91453, 2007, 'bmc', 'Multiple non-collinear TF-map alignments of promoter regions', 'Blanco, Enrique|Guigó, Roderic|Messeguer, Xavier', 'Grup dAlgorísmica i Genètica, Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, C/Jordi Girona, 1-3, Barcelona, Catalonia, Spain. eblanco@imim.es <eblanco@imim.es>|Grup dAlgorísmica i Genètica, Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, C/Jordi Girona, 1-3, Barcelona, Catalonia, Spain. eblanco@imim.es <eblanco@imim.es>|Grup dAlgorísmica i Genètica, Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, C/Jordi Girona, 1-3, Barcelona, Catalonia, Spain. eblanco@imim.es <eblanco@imim.es>', 'Spain|Spain|Spain', 9, 'Animals|Base Sequence|Chickens|Humans|Mice|Nucleotide Mapping|Promoter Regions, Genetic|Sequence Alignment|Transcription Factors|Zebrafish', 'Comparative Study', '10.1186/1471-2105-8-138', '17456238', 'The analysis of the promoter sequence of genes with similar expression patterns is a basic tool to annotate common regulatory elements. Multiple sequence alignments are on the basis of most comparative approaches. The characterization of regulatory regions from co-expressed genes at the sequence level, however, does not yield satisfactory results in many occasions as promoter regions of genes sharing similar expression programs often do not show nucleotide sequence conservation.'),
(91454, 2007, 'bmc', 'Toward the automated generation of genome-scale metabolic networks in the SEED', 'DeJongh, Matthew|Formsma, Kevin|Boillot, Paul|Gould, John|Rycenga, Matthew|Best, Aaron', 'Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>|Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>|Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>|Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>|Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>|Department of Computer Science, Hope College, Holland, MI, USA. dejongh@hope.edu <dejongh@hope.edu>', 'United States|United States|United States|United States|United States|United States', 0, 'Genome|Genome, Bacterial|Metabolic Networks and Pathways|Software Design', 'Comparative Study', '10.1186/1471-2105-8-139', '17462086', 'Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process.'),
(91455, 2007, 'bmc', 'Lower bounds on multiple sequence alignment using exact 3-way alignment', 'Colbourn, Charles J|Kumar, Sudhir', 'Center for Evolutionary Functional Genomics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5301, USA. Charles.Colbourn@asu.edu|Center for Evolutionary Functional Genomics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5301, USA. Charles.Colbourn@asu.edu', 'United States|United States', 2, 'Algorithms|Base Sequence|DNA|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-8-140', '17470273', 'Multiple sequence alignment is fundamental. Exponential growth in computation time appears to be inevitable when an optimal alignment is required for many sequences. Exact costs of optimum alignments are therefore rarely computed. Consequently much effort has been invested in algorithms for alignment that are heuristic, or explore a restricted class of solutions. These give an upper bound on the alignment cost, but it is equally important to determine the quality of the solution obtained. In the absence of an optimal alignment with which to compare, lower bounds may be calculated to assess the quality of the alignment. As more effort is invested in improving upper bounds (alignment algorithms), it is therefore important to improve lower bounds as well. Although numerous cost metrics can be used to determine the quality of an alignment, many are based on sum-of-pairs (SP) measures and their generalizations.'),
(91456, 2007, 'bmc', 'Relating destabilizing regions to known functional sites in proteins', 'Dessailly, Benoît H|Lensink, Marc F|Wodak, Shoshana J', 'Service de Conformation des Macromolécules Biologiques, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bruxelles, Belgium. benoit@scmbb.ulb.ac.be <benoit@scmbb.ulb.ac.be>|Service de Conformation des Macromolécules Biologiques, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bruxelles, Belgium. benoit@scmbb.ulb.ac.be <benoit@scmbb.ulb.ac.be>|Service de Conformation des Macromolécules Biologiques, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bruxelles, Belgium. benoit@scmbb.ulb.ac.be <benoit@scmbb.ulb.ac.be>', 'Belgium|Belgium|Belgium', 25, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-141', '17470296', 'Most methods for predicting functional sites in protein 3D structures, rely on information on related proteins and cannot be applied to proteins with no known relatives. Another limitation of these methods is the lack of a well annotated set of functional sites to use as benchmark for validating their predictions. Experimental findings and theoretical considerations suggest that residues involved in function often contribute unfavorably to the native state stability. We examine the possibility of systematically exploiting this intrinsic property to identify functional sites using an original procedure that detects destabilizing regions in protein structures. In addition, to relate destabilizing regions to known functional sites, a novel benchmark consisting of a diverse set of hand-curated protein functional sites is derived.'),
(91457, 2007, 'bmc', 'Pre-processing Agilent microarray data', 'Zahurak, Marianna|Parmigiani, Giovanni|Yu, Wayne|Scharpf, Robert B|Berman, David|Schaeffer, Edward|Shabbeer, Shabana|Cope, Leslie', 'Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu|Johns Hopkins University School of Medicine, Oncology Biostatistics, Baltimore, MD 21205, USA. zahurma@jhmi.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Cell Line, Tumor|Databases, Genetic|Dogs|Gene Expression Profiling|Humans|Mice|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-142', '17472750', 'Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression using Agilent arrays and to compare Agilents Feature Extraction software with pre-processing methods that have become the standard for normalization of cDNA arrays. These include log transformation followed by loess normalization with or without background subtraction and often a between array scale normalization procedure. The larger goal is to define best study design and pre-processing practices for Agilent arrays, and we offer some suggestions.'),
(91458, 2007, 'bmc', 'VSGdb: a database for trypanosome variant surface glycoproteins, a large and diverse family of coiled coil proteins', 'Marcello, Lucio|Menon, Suraj|Ward, Pauline|Wilkes, Jonathan M|Jones, Nicola G|Carrington, Mark|Barry, J David', 'Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>|Wellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow Biomedical Research Centre, Glasgow, UK. l.marcello.1@research.gla.ac.uk <l.marcello.1@research.gla.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 20, 'Base Sequence|Databases, Factual|Molecular Sequence Data|Protein Structure, Tertiary|Sequence Analysis, DNA|Variant Surface Glycoproteins, Trypanosoma', 'Comparative Study', '10.1186/1471-2105-8-143', '17474977', 'Trypanosomes are coated with a variant surface glycoprotein (VSG) that is so densely packed that it physically protects underlying proteins from effectors of the host immune system. Periodically cells expressing a distinct VSG arise in a population and thereby evade immunity. The main structural feature of VSGs are two long alpha-helices that form a coiled coil, and sets of relatively unstructured loops that are distal to the plasma membrane and contain most or all of the protective epitopes. The primary structure of different VSGs is highly variable, typically displaying only ~20% identity with each other. The genome has nearly 2000 VSG genes, which are located in subtelomeres. Only one VSG gene is expressed at a time, and switching between VSGs primarily involves gene conversion events. The archive of silent VSGs undergoes diversifying evolution rapidly, also involving gene conversion. The VSG family is a paradigm for alpha helical coiled coil structures, epitope variation and GPI-anchor signals. At the DNA level, the genes are a paradigm for diversifying evolutionary processes and for the role of subtelomeres and recombination mechanisms in generation of diversity in multigene families. To enable ready availability of VSG sequences for addressing these general questions, and trypanosome-specific questions, we have created VSGdb, a database of all known sequences.'),
(91459, 2007, 'bmc', 'Recursive cluster elimination (RCE) for classification and feature selection from gene expression data', 'Yousef, Malik|Jung, Segun|Showe, Louise C|Showe, Michael K', 'The Wistar Institute, Systems Biology Division, Philadelphia, PA 19104, USA. yousef@wistar.org <yousef@wistar.org>|The Wistar Institute, Systems Biology Division, Philadelphia, PA 19104, USA. yousef@wistar.org <yousef@wistar.org>|The Wistar Institute, Systems Biology Division, Philadelphia, PA 19104, USA. yousef@wistar.org <yousef@wistar.org>|The Wistar Institute, Systems Biology Division, Philadelphia, PA 19104, USA. yousef@wistar.org <yousef@wistar.org>', 'United States|United States|United States|United States', 59, 'Databases, Genetic|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Head and Neck Neoplasms|Humans|Male|Multigene Family|Prostatic Neoplasms', 'Comparative Study', '10.1186/1471-2105-8-144', '17474999', 'Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE) rather than recursive feature elimination (RFE). We have tested this algorithm on six datasets and compared its performance with that of two related classification procedures with RFE.'),
(91460, 2007, 'bmc', 'A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array', 'Yu, Tianwei|Ye, Hui|Sun, Wei|Li, Ker-Chau|Chen, Zugen|Jacobs, Sharoni|Bailey, Dione K|Wong, David T|Zhou, Xiaofeng', 'Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu|Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. tyu8@sph.emory.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cell Line, Tumor|Chromosome Breakage|Gene Amplification|Gene Deletion|Genome, Human|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Comparative Study', '10.1186/1471-2105-8-145', '17477871', 'DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required.'),
(91461, 2007, 'bmc', 'Analysis of probe level patterns in Affymetrix microarray data', 'Cambon, Alexander C|Khalyfa, Abdelnaby|Cooper, Nigel G F|Thompson, Caryn M', 'Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA. accamb01@louisville.edu <accamb01@louisville.edu>|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA. accamb01@louisville.edu <accamb01@louisville.edu>|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA. accamb01@louisville.edu <accamb01@louisville.edu>|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA. accamb01@louisville.edu <accamb01@louisville.edu>', 'United States|United States|United States|United States', 0, 'Animals|Cells, Cultured|Molecular Probe Techniques|Molecular Probes|Oligonucleotide Array Sequence Analysis|Rats', 'Comparative Study', '10.1186/1471-2105-8-146', '17480226', 'Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix Genechip microarray data, including RMA, GCRMA and Model Based Expression Index (MBEI), summarize probe signal intensity data to generate a single measure of expression for each transcript on the array. In contrast, other methods are applied directly to probe intensities, negating the need for a summarization step.'),
(91462, 2007, 'bmc', 'Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins', 'Dong, Qiwen|Wang, Xiaolong|Lin, Lei|Guan, Yi', 'School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. qwdong@insun.hit.edu.cn|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. qwdong@insun.hit.edu.cn|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. qwdong@insun.hit.edu.cn|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. qwdong@insun.hit.edu.cn', 'China|China|China|China', 42, 'Amino Acids|Binding Sites|Computational Biology|Databases, Protein|Evolution, Molecular|Models, Molecular|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping|Proteins', 'Comparative Study', '10.1186/1471-2105-8-147', '17480235', 'Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residue preferences have been widely used in many studies but the results are often not satisfactory. Although different amino acid compositions among the interaction sites of different complexes have been observed, such differences have not been integrated into the prediction process. Furthermore, the evolution information has not been exploited to achieve a more powerful propensity.'),
(91463, 2007, 'bmc', 'primetv: a viewer for reconciled trees', 'Sennblad, Bengt|Schreil, Eva|Berglund Sonnhammer, Ann-Charlotte|Lagergren, Jens|Arvestad, Lars', 'Stockholm Bioinformatics Center and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. bengt.sennblad@sbc.su.se <bengt.sennblad@sbc.su.se>|Stockholm Bioinformatics Center and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. bengt.sennblad@sbc.su.se <bengt.sennblad@sbc.su.se>|Stockholm Bioinformatics Center and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. bengt.sennblad@sbc.su.se <bengt.sennblad@sbc.su.se>|Stockholm Bioinformatics Center and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. bengt.sennblad@sbc.su.se <bengt.sennblad@sbc.su.se>|Stockholm Bioinformatics Center and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. bengt.sennblad@sbc.su.se <bengt.sennblad@sbc.su.se>', 'Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Algorithms|Animals|Classification|Evolution, Molecular|Internet|Major Histocompatibility Complex|Phylogeny|Primates|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-148', '17484781', 'Evolutionary processes, such as gene family evolution or parasite-host co-speciation, can often be viewed as a tree evolving inside another tree. Relating two given trees under such a constraint is known as reconciling them. Adequate software tools for generating illustrations of tree reconciliations are instrumental for presenting and communicating results and ideas regarding these phenomena. Available visualization tools have been limited to illustrations of the most parsimonious reconciliation. However, there exists a plethora of biologically relevant non-parsimonious reconciliations. Illustrations of these general reconciliations may not be achieved without manual editing.'),
(91464, 2007, 'bmc', 'Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli', 'Schramm, Gunnar|Zapatka, Marc|Eils, Roland|König, Rainer', 'Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. g.schramm@dkfz.de <g.schramm@dkfz.de>|Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. g.schramm@dkfz.de <g.schramm@dkfz.de>|Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. g.schramm@dkfz.de <g.schramm@dkfz.de>|Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. g.schramm@dkfz.de <g.schramm@dkfz.de>', 'Germany|Germany|Germany|Germany', 10, 'Cluster Analysis|Escherichia coli|Gene Expression Regulation, Bacterial|Genes, Switch|Metabolic Networks and Pathways|Oxygen', 'Comparative Study', '10.1186/1471-2105-8-149', '17488495', 'Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation of the metabolism when cells adapt to environmental changes, whole genome gene expression profiles can be analysed. Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks.'),
(91465, 2007, 'bmc', 'Detecting multivariate differentially expressed genes', 'Nilsson, Roland|Peña, José M|Björkegren, Johan|Tegnér, Jesper', 'Computational Biology, Department of Physics, Linköping University, Linköping, Sweden. rolle@ifm.liu.se|Computational Biology, Department of Physics, Linköping University, Linköping, Sweden. rolle@ifm.liu.se|Computational Biology, Department of Physics, Linköping University, Linköping, Sweden. rolle@ifm.liu.se|Computational Biology, Department of Physics, Linköping University, Linköping, Sweden. rolle@ifm.liu.se', 'Sweden|Sweden|Sweden|Sweden', 21, 'Algorithms|Breast Neoplasms|Databases, Genetic|Diabetes Mellitus|Female|Gene Expression Regulation|Humans|Multivariate Analysis|Protein Array Analysis', 'Comparative Study', '10.1186/1471-2105-8-150', '17490475', 'Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariate in nature. Yet, current statistical methods for detecting differential expression merely consider the univariate difference in expression level of each gene in isolation, thus potentially neglecting many genes of biological importance.'),
(91466, 2007, 'bmc', 'Tracembler--software for in-silico chromosome walking in unassembled genomes', 'Dong, Qunfeng|Wilkerson, Matthew D|Brendel, Volker', 'Department of Genetics, Development & Cell Biology, Iowa State University, Ames, Iowa 50011, USA. qfdong@cgb.indiana.edu <qfdong@cgb.indiana.edu>|Department of Genetics, Development & Cell Biology, Iowa State University, Ames, Iowa 50011, USA. qfdong@cgb.indiana.edu <qfdong@cgb.indiana.edu>|Department of Genetics, Development & Cell Biology, Iowa State University, Ames, Iowa 50011, USA. qfdong@cgb.indiana.edu <qfdong@cgb.indiana.edu>', 'United States|United States|United States', 0, 'Algorithms|Chromosome Walking|Genome Components|Information Storage and Retrieval|Medicago truncatula|Sequence Alignment|Sequence Homology|Software|Software Validation|Soybeans|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-151', '17490482', 'Whole genome shotgun sequencing produces increasingly higher coverage of a genome with random sequence reads. Progressive whole genome assembly and eventual finishing sequencing is a process that typically takes several years for large eukaryotic genomes. In the interim, all sequence reads of public sequencing projects are made available in repositories such as the NCBI Trace Archive. For a particular locus, sequencing coverage may be high enough early on to produce a reliable local genome assembly. We have developed software, Tracembler, that facilitates in silico chromosome walking by recursively assembling reads of a selected species from the NCBI Trace Archive starting with reads that significantly match sequence seeds supplied by the user.'),
(91467, 2007, 'bmc', 'Comparative analysis of long DNA sequences by per element information content using different contexts', 'Dix, Trevor I|Powell, David R|Allison, Lloyd|Bernal, Julie|Jaeger, Samira|Stern, Linda', 'Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au|Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au|Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au|Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au|Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au|Faculty of Information Technology, Monash University, Clayton, Australia. trevor.dix@infotech.monash.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 32, 'Algorithms|Base Sequence|DNA|Information Storage and Retrieval|Information Theory|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1186/1471-2105-8-S2-S10', '17493248', 'Features of a DNA sequence can be found by compressing the sequence under a suitable model, good compression implies low information content. Good DNA compression models consider repetition, differences between repeats, and base distributions. From a linear DNA sequence, a compression model can produce a linear information sequence. Linear space complexity is important when exploring long DNA sequences of the order of millions of bases. Compressing a sequence in isolation will include information on self-repetition. Whereas compressing a sequence Y in the context of another X can find what new information X gives about Y. This paper presents a methodology for performing comparative analysis to find features exposed by such models.'),
(91468, 2007, 'bmc', 'Methods for estimating human endogenous retrovirus activities from EST databases', 'Oja, Merja|Peltonen, Jaakko|Blomberg, Jonas|Kaski, Samuel', 'Department of Computer Science, University of Helsinki, University of Helsinki, Finland. merja.oja@tkk.fi|Department of Computer Science, University of Helsinki, University of Helsinki, Finland. merja.oja@tkk.fi|Department of Computer Science, University of Helsinki, University of Helsinki, Finland. merja.oja@tkk.fi|Department of Computer Science, University of Helsinki, University of Helsinki, Finland. merja.oja@tkk.fi', 'Finland|Finland|Finland|Finland', 26, 'Algorithms|Chromosome Mapping|Databases, Genetic|Evolution, Molecular|Expressed Sequence Tags|Genome, Viral|Humans|Markov Chains|Retroviridae|Species Specificity|Virus Activation', 'Journal Article', '10.1186/1471-2105-8-S2-S11', '17493249', 'Human endogenous retroviruses (HERVs) are surviving traces of ancient retrovirus infections and now reside within the human DNA. Recently HERV expression has been detected in both normal tissues and diseased patients. However, the activities (expression levels) of individual HERV sequences are mostly unknown.'),
(91469, 2007, 'bmc', 'Improved functional prediction of proteins by learning kernel combinations in multilabel settings', 'Roth, Volker|Fischer, Bernd', 'ETH Zurich, Institute of Computational Science, Zurich, Switzerland. vroth@inf.ethz.ch|ETH Zurich, Institute of Computational Science, Zurich, Switzerland. vroth@inf.ethz.ch', 'Switzerland|Switzerland', 19, 'Algorithms|Artificial Intelligence|Computer Simulation|Fungal Proteins|Models, Biological|Sequence Analysis, Protein|Signal Transduction|Structure-Activity Relationship|Yeasts', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S12', '17493250', 'We develop a probabilistic model for combining kernel matrices to predict the function of proteins. It extends previous approaches in that it can handle multiple labels which naturally appear in the context of protein function.'),
(91470, 2007, 'bmc', 'Bayesian model-based inference of transcription factor activity', 'Rogers, Simon|Khanin, Raya|Girolami, Mark', 'Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK. srogers@dcs.gla.ac.uk|Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK. srogers@dcs.gla.ac.uk|Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK. srogers@dcs.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 47, 'Algorithms|Artificial Intelligence|Bayes Theorem|Computer Simulation|Models, Biological|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1186/1471-2105-8-S2-S2', '17493251', 'In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is considered to be an accurate surrogate for the true activity of the protein it produces. There are many instances where this is inaccurate due to post-translational modifications of the transcription factor protein. Inference of the activity of the transcription factor from the expression of its targets has predominantly involved linear models that do not reflect the nonlinear nature of transcription. We extend a recent approach to inferring the transcription factor activity based on nonlinear Michaelis-Menten kinetics of transcription from maximum likelihood to fully Bayesian inference and give an example of how the model can be further developed.'),
(91471, 2007, 'bmc', 'Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process', 'Opgen-Rhein, Rainer|Strimmer, Korbinian', 'Department of Statistics, Ludwig-Maximilians-Universität München, München, Germany. opgen-rhein@stat.uni-muenchen.de|Department of Statistics, Ludwig-Maximilians-Universität München, München, Germany. opgen-rhein@stat.uni-muenchen.de', 'Germany|Germany', 94, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Regulation|Models, Biological|Pattern Recognition, Automated|Proteome|Regression Analysis|Signal Transduction|Systems Biology|Time Factors', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S3', '17493252', 'Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning these networks is challenging due to the low sample size and high dimensionality of genomic data.'),
(91472, 2007, 'bmc', 'Inferring biological networks with output kernel trees', 'Geurts, Pierre|Touleimat, Nizar|Dutreix, Marie|dAlché-Buc, Florence', 'IBISC FRE CNRS 2873 & Epigenomics project, GENOPOLE, Evry, France. p.geurts@ulg.ac.be|IBISC FRE CNRS 2873 & Epigenomics project, GENOPOLE, Evry, France. p.geurts@ulg.ac.be|IBISC FRE CNRS 2873 & Epigenomics project, GENOPOLE, Evry, France. p.geurts@ulg.ac.be|IBISC FRE CNRS 2873 & Epigenomics project, GENOPOLE, Evry, France. p.geurts@ulg.ac.be', 'France|France|France|France', 25, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Regulation|Models, Biological|Pattern Recognition, Automated|Proteome|Regression Analysis|Signal Transduction|Systems Biology|Time Factors', 'Journal Article', '10.1186/1471-2105-8-S2-S4', '17493253', 'Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem are important to complement high-throughput technologies and to help biologists in designing new experiments. In this work, we focus on the completion of a biological network from various sources of experimental data.'),
(91473, 2007, 'bmc', 'Validating module network learning algorithms using simulated data', 'Michoel, Tom|Maere, Steven|Bonnet, Eric|Joshi, Anagha|Saeys, Yvan|Van den Bulcke, Tim|Van Leemput, Koenraad|van Remortel, Piet|Kuiper, Martin|Marchal, Kathleen|Van de Peer, Yves', 'Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be|Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB/Ghent University, Ghent, Belgium. tom.michoel@psb.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 30, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Regulation|Models, Biological|Pattern Recognition, Automated|Proteome|Signal Transduction|Software|Software Validation|Systems Biology', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S5', '17493254', 'In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Despite the demonstrated success of such algorithms in uncovering biologically relevant regulatory relations, further developments in the area are hampered by a lack of tools to compare the performance of alternative module network learning strategies. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance.'),
(91474, 2007, 'bmc', 'Robust imputation method for missing values in microarray data', 'Yoon, Dankyu|Lee, Eun-Kyung|Park, Taesung', 'Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea. avanti@chol.com|Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea. avanti@chol.com|Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea. avanti@chol.com', '-|-|-', 32, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Information Storage and Retrieval|Least-Squares Analysis|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S6', '17493255', 'When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis cannot be applied when the data have missing values. Numerous imputation algorithms have been proposed to estimate the missing values. In this study, we develop a robust least squares estimation with principal components (RLSP) method by extending the local least square imputation (LLSimpute) method. The basic idea of our method is to employ quantile regression to estimate the missing values, using the estimated principal components of a selected set of similar genes.'),
(91475, 2007, 'bmc', 'Model order selection for bio-molecular data clustering', 'Bertoni, Alberto|Valentini, Giorgio', 'DSI, Dipartimento di Scienze dellInformazione, Università degli Studi di Milano, Milano, Italy. bertoni@dsi.unimi.it|DSI, Dipartimento di Scienze dellInformazione, Università degli Studi di Milano, Milano, Italy. bertoni@dsi.unimi.it', 'Italy|Italy', 33, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-8-S2-S7', '17493256', 'Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically detect the natural number of clusters underlying the data, and in many cases we have no enough a priori biological knowledge to evaluate both the number of clusters as well as their validity. Recently several methods based on the concept of stability have been proposed to estimate the optimal number of clusters, but despite their successful application to the analysis of complex bio-molecular data, the assessment of the statistical significance of the discovered clustering solutions and the detection of multiple structures simultaneously present in high-dimensional bio-molecular data are still major problems.'),
(91476, 2007, 'bmc', 'A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data', 'Vehtari, Aki|Mäkinen, Ville-Petteri|Soininen, Pasi|Ingman, Petri|Mäkelä, Sanna M|Savolainen, Markku J|Hannuksela, Minna L|Kaski, Kimmo|Ala-Korpela, Mika', 'Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi|Laboratory of Computational Engineering, Systems Biology and Bioinformation Technology, Helsinki University of Technology, Finland. aki.vehtari@hut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 46, 'Artificial Intelligence|Bayes Theorem|Biomarkers|Blood Chemical Analysis|Coronary Disease|Diagnosis, Computer-Assisted|Humans|Lipoproteins|Magnetic Resonance Spectroscopy|Pattern Recognition, Automated|Protons|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S8', '17493257', 'A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk assessment and diagnostics. Here we focus on clinically relevant estimation of lipoprotein lipids by 1H NMR spectroscopy of serum.'),
(91477, 2007, 'bmc', 'Constrained hidden Markov models for population-based haplotyping', 'Landwehr, Niels|Mielikäinen, Taneli|Eronen, Lauri|Toivonen, Hannu|Mannila, Heikki', 'Machine Learning Lab, Department of Computer Science, Albert-Ludwigs-University Freiburg, Germany. landwehr@informatik.uni-freiburg.de|Machine Learning Lab, Department of Computer Science, Albert-Ludwigs-University Freiburg, Germany. landwehr@informatik.uni-freiburg.de|Machine Learning Lab, Department of Computer Science, Albert-Ludwigs-University Freiburg, Germany. landwehr@informatik.uni-freiburg.de|Machine Learning Lab, Department of Computer Science, Albert-Ludwigs-University Freiburg, Germany. landwehr@informatik.uni-freiburg.de|Machine Learning Lab, Department of Computer Science, Albert-Ludwigs-University Freiburg, Germany. landwehr@informatik.uni-freiburg.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Genetic Linkage|Genetics, Population|Haplotypes|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-8-S2-S9', '17493258', 'Haplotype Reconstruction is the problem of resolving the hidden phase information in genotype data obtained from laboratory measurements. Solving this problem is an important intermediate step in gene association studies, which seek to uncover the genetic basis of complex diseases. We propose a novel approach for haplotype reconstruction based on constrained hidden Markov models. Models are constructed by incrementally refining and regularizing the structure of a simple generative model for genotype data under Hardy-Weinberg equilibrium.'),
(91478, 2007, 'bmc', 'Reconstruction of human protein interolog network using evolutionary conserved network', 'Huang, Tao-Wei|Lin, Chung-Yen|Kao, Cheng-Yan', 'Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. d90016@csie.ntu.edu.tw <d90016@csie.ntu.edu.tw>|Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. d90016@csie.ntu.edu.tw <d90016@csie.ntu.edu.tw>|Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. d90016@csie.ntu.edu.tw <d90016@csie.ntu.edu.tw>', '-|-|-', 28, 'Computational Biology|Databases, Protein|Evolution, Molecular|Humans|Protein Interaction Mapping|Proteins|Proteomics|Research Design', 'Journal Article', '10.1186/1471-2105-8-152', '17493278', 'The recent increase in the use of high-throughput two-hybrid analysis has generated large quantities of data on protein interactions. Specifically, the availability of information about experimental protein-protein interactions and other protein features on the Internet enables human protein-protein interactions to be computationally predicted from co-evolution events (interolog). This study also considers other protein interaction features, including sub-cellular localization, tissue-specificity, the cell-cycle stage and domain-domain combination. Computational methods need to be developed to integrate these heterogeneous biological data to facilitate the maximum accuracy of the human protein interaction prediction.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91479, 2007, 'bmc', 'Advancing translational research with the Semantic Web', 'Ruttenberg, Alan|Clark, Tim|Bug, William|Samwald, Matthias|Bodenreider, Olivier|Chen, Helen|Doherty, Donald|Forsberg, Kerstin|Gao, Yong|Kashyap, Vipul|Kinoshita, June|Luciano, Joanne|Marshall, M Scott|Ogbuji, Chimezie|Rees, Jonathan|Stephens, Susie|Wong, Gwendolyn T|Wu, Elizabeth|Zaccagnini, Davide|Hongsermeier, Tonya|Neumann, Eric|Herman, Ivan|Cheung, Kei-Hoi', 'Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>|Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|Uni', 199, 'Biomedical Research|Databases, Factual|Documentation|Information Dissemination|Information Storage and Retrieval|Internationality|Internet|Natural Language Processing|Neurosciences|Research|Research Design|Semantics', 'Journal Article', '10.1186/1471-2105-8-S3-S2', '17493285', 'A fundamental goal of the U.S. National Institute of Health (NIH) Roadmap is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature.'),
(91480, 2007, 'bmc', 'e-Science and biological pathway semantics', 'Luciano, Joanne S|Stevens, Robert D', 'Genetics Department, Harvard Medical School, Boston, MA 02115, USA. jluciano@genetics.med.harvard.edu|Genetics Department, Harvard Medical School, Boston, MA 02115, USA. jluciano@genetics.med.harvard.edu', 'United States|United States', 37, 'Databases, Protein|Documentation|Information Dissemination|Information Storage and Retrieval|Internationality|Internet|Natural Language Processing|Proteome|Research|Research Design|Science|Semantics|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-S3-S3', '17493286', 'The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science.'),
(91481, 2007, 'bmc', 'AlzPharm: integration of neurodegeneration data using RDF', 'Lam, Hugo Y K|Marenco, Luis|Clark, Tim|Gao, Yong|Kinoshita, June|Shepherd, Gordon|Miller, Perry|Wu, Elizabeth|Wong, Gwendolyn T|Liu, Nian|Crasto, Chiquito|Morse, Thomas|Stephens, Susie|Cheung, Kei-Hoi', 'Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Hugo.YK.Lam@yale.edu <Hugo.YK.Lam@yale.edu>', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 41, 'Brain|Database Management Systems|Databases, Factual|Documentation|Humans|Information Dissemination|Information Storage and Retrieval|Internationality|Internet|Natural Language Processing|Nerve Tissue Proteins|Neurodegenerative Diseases|Neurosciences|Pilot Projects|Research|Research Design|Semantics|Systems Integration', 'Journal Article', '10.1186/1471-2105-8-S3-S4', '17493287', 'Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data.'),
(91482, 2007, 'bmc', 'LinkHub: a Semantic Web system that facilitates cross-database queries and information retrieval in proteomics', 'Smith, Andrew K|Cheung, Kei-Hoi|Yip, Kevin Y|Schultz, Martin|Gerstein, Mark K', 'Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA. andrew.smith@yale.edu|Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA. andrew.smith@yale.edu|Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA. andrew.smith@yale.edu|Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA. andrew.smith@yale.edu|Department of Computer Science, Yale University, New Haven, Connecticut, 06520 USA. andrew.smith@yale.edu', 'United States|United States|United States|United States|United States', 33, 'Database Management Systems|Databases, Protein|Documentation|Information Dissemination|Information Storage and Retrieval|Internationality|Internet|Natural Language Processing|Proteomics|Semantics|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S3-S5', '17493288', 'A key abstraction in representing proteomics knowledge is the notion of unique identifiers for individual entities (e.g. proteins) and the massive graph of relationships among them. These relationships are sometimes simple (e.g. synonyms) but are often more complex (e.g. one-to-many relationships in protein family membership).'),
(91483, 2007, 'bmc', 'Towards Semantic e-Science for Traditional Chinese Medicine', 'Chen, Huajun|Mao, Yuxin|Zheng, Xiaoqing|Cui, Meng|Feng, Yi|Deng, Shuiguang|Yin, Aining|Zhou, Chunying|Tang, Jinming|Jiang, Xiaohong|Wu, Zhaohui', 'College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn|College of Computer Science, Zhejiang University, Hangzhou, PR China. huajunsir@zju.edu.cn', 'China|China|China|China|China|China|China|China|China|China|China', 27, 'Database Management Systems|Databases, Factual|Documentation|Information Dissemination|Information Storage and Retrieval|Internationality|Internet|Medicine, Chinese Traditional|Natural Language Processing|Science|Semantics|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S3-S6', '17493289', 'Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science.'),
(91484, 2007, 'bmc', 'Evaluation of high-throughput functional categorization of human disease genes', 'Chen, James L|Liu, Yang|Sam, Lee T|Li, Jianrong|Lussier, Yves A', 'Department of Medicine, Georgetown University Hospital, Washington, DC, USA. jlcb@gunet.georgetown.edu|Department of Medicine, Georgetown University Hospital, Washington, DC, USA. jlcb@gunet.georgetown.edu|Department of Medicine, Georgetown University Hospital, Washington, DC, USA. jlcb@gunet.georgetown.edu|Department of Medicine, Georgetown University Hospital, Washington, DC, USA. jlcb@gunet.georgetown.edu|Department of Medicine, Georgetown University Hospital, Washington, DC, USA. jlcb@gunet.georgetown.edu', 'United States|United States|United States|United States|United States', 0, 'Computer Simulation|Database Management Systems|Databases, Genetic|Genetic Diseases, Inborn|Genetic Predisposition to Disease|Humans|Information Storage and Retrieval|Models, Genetic|Natural Language Processing|Proteome', 'Journal Article', '10.1186/1471-2105-8-S3-S7', '17493290', 'Biological data that are well-organized by an ontology, such as Gene Ontology, enables high-throughput availability of the semantic web. It can also be used to facilitate high throughput classification of biomedical information. However, to our knowledge, no evaluation has been published on automating classifications of human diseases genes using Gene Ontology. In this study, we evaluate automated classifications of well-defined human disease genes using their Gene Ontology annotations and compared them to a gold standard. This gold standard was independently conceived by Valles research group, and contains 923 human disease genes organized in 14 categories of protein function.'),
(91485, 2007, 'bmc', 'How accurate and statistically robust are catalytic site predictions based on closeness centrality?', 'Chea, Eric|Livesay, Dennis R', 'Department of Biological Sciences, California State Polytechnic University, Pomona, CA 91768, USA. erc2009@med.cornell.edu <erc2009@med.cornell.edu>|Department of Biological Sciences, California State Polytechnic University, Pomona, CA 91768, USA. erc2009@med.cornell.edu <erc2009@med.cornell.edu>', 'United States|United States', 0, 'Amino Acid Sequence|Binding Sites|Catalytic Domain|Databases, Factual|Models, Statistical|Predictive Value of Tests|Protein Structure, Secondary|Protein Structure, Tertiary|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-153', '17498304', 'We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid alpha-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex i and all other vertices.'),
(91486, 2007, 'bmc', 'Unexpected observations after mapping LongSAGE tags to the human genome', 'Keime, Céline|Sémon, Marie|Mouchiroud, Dominique|Duret, Laurent|Gandrillon, Olivier', 'Université de Lyon, Lyon, France. keime@biomserv.univ-lyon1.fr|Université de Lyon, Lyon, France. keime@biomserv.univ-lyon1.fr|Université de Lyon, Lyon, France. keime@biomserv.univ-lyon1.fr|Université de Lyon, Lyon, France. keime@biomserv.univ-lyon1.fr|Université de Lyon, Lyon, France. keime@biomserv.univ-lyon1.fr', 'France|France|France|France|France', 15, 'Chromosome Mapping|Gene Library|Genome, Human|Humans|Sequence Tagged Sites', 'Journal Article', '10.1186/1471-2105-8-154', '17504516', 'SAGE has been used widely to study the expression of known transcripts, but much less to annotate new transcribed regions. LongSAGE produces tags that are sufficiently long to be reliably mapped to a whole-genome sequence. Here we used this property to study the position of human LongSAGE tags obtained from all public libraries. We focused mainly on tags that do not map to known transcripts.'),
(91487, 2007, 'bmc', 'TAP score: torsion angle propensity normalization applied to local protein structure evaluation', 'Tosatto, Silvio C E|Battistutta, Roberto', 'Dept. of Biology and CRIBI Biotechnology Centre, University of Padova, Italy. silvio.tosatto@unipd.it|Dept. of Biology and CRIBI Biotechnology Centre, University of Padova, Italy. silvio.tosatto@unipd.it', 'Italy|Italy', 0, 'Computational Biology|Databases, Protein|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Torsion Abnormality', 'Comparative Study', '10.1186/1471-2105-8-155', '17504537', 'Experimentally determined protein structures may contain errors and require validation. Conformational criteria based on the Ramachandran plot are mainly used to distinguish between distorted and adequately refined models. While the readily available criteria are sufficient to detect totally wrong structures, establishing the more subtle differences between plausible structures remains more challenging.'),
(91488, 2007, 'bmc', 'The Deuterator: software for the determination of backbone amide deuterium levels from H/D exchange MS data', 'Pascal, B D|Chalmers, M J|Busby, S A|Mader, C C|Southern, M R|Tsinoremas, N F|Griffin, P R', 'Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>|Translational Research Institute, The Scripps Research Institute--Scripps Florida, Jupiter, FL 33458, USA. bpascal@scripps.edu <bpascal@scripps.edu>', 'United States|United States|United States|United States|United States|United States|United States', 61, 'Amides|Amino Acid Sequence|Deuterium|Deuterium Exchange Measurement|Hydrogen|Mass Spectrometry|Molecular Sequence Data|Peptide Fragments|Software', 'Journal Article', '10.1186/1471-2105-8-156', '17506883', 'The combination of mass spectrometry and solution phase amide hydrogen/deuterium exchange (H/D exchange) experiments is an effective method for characterizing protein dynamics, and protein-protein or protein-ligand interactions. Despite methodological advancements and improvements in instrumentation and automation, data analysis and display remains a tedious process. The factors that contribute to this bottleneck are the large number of data points produced in a typical experiment, each requiring manual curation and validation, and then calculation of the level of backbone amide exchange. Tools have become available that address some of these issues, but lack sufficient integration, functionality, and accessibility required to address the needs of the H/D exchange community. To date there is no software for the analysis of H/D exchange data that comprehensively addresses these issues.'),
(91489, 2007, 'bmc', 'Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures', 'Lu, Xin|Perkins, David L', 'Department of Family and Preventive Medicine, UC San Diego, La Jolla, CA 92093, USA. xinlu@ucsd.edu|Department of Family and Preventive Medicine, UC San Diego, La Jolla, CA 92093, USA. xinlu@ucsd.edu', 'United States|United States', 0, 'Algorithms|Data Interpretation, Statistical|Databases, Genetic|False Positive Reactions|Gene Expression Profiling|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Statistics as Topic', 'Evaluation Studies', '10.1186/1471-2105-8-157', '17509157', 'When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff between controlling FDR and maximizing power. Several methods have been proposed, such as the q-value method, to estimate the proportion of true null hypothesis among the tested hypotheses, and use this estimation in the control of FDR. These methods usually depend on the assumption that the test statistics are independent (or only weakly correlated). However, many types of data, for example microarray data, often contain large scale correlation structures. Our objective was to develop methods to control the FDR while maintaining a greater level of power in highly correlated datasets by improving the estimation of the proportion of null hypotheses.'),
(91490, 2007, 'bmc', 'TBMap: a taxonomic perspective on the phylogenetic database TreeBASE', 'Page, Roderic D M', 'Division of Environmental and Evolutionary Biology, Institute of Biomedical and Life Sciences, Graham Kerr Building, University of Glasgow, Glasgow, UK. r.page@bio.gla.ac.uk', 'United Kingdom', 16, 'Base Sequence|Chromosome Mapping|Classification|Database Management Systems|Databases, Genetic|Documentation|Models, Genetic|Molecular Sequence Data|Phylogeny|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-158', '17511869', 'TreeBASE is currently the only available large-scale database of published organismal phylogenies. Its utility is hampered by a lack of taxonomic consistency, both within the database, and with names of organisms in external genomic, specimen, and taxonomic databases. The extent to which the phylogenetic knowledge in TreeBASE becomes integrated with these other sources is limited by this lack of consistency.'),
(91491, 2007, 'bmc', 'A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana', 'Pertea, Mihaela|Mount, Stephen M|Salzberg, Steven L', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. mpertea@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. mpertea@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. mpertea@umiacs.umd.edu', 'United States|United States|United States', 55, 'Alternative Splicing|Arabidopsis|Computational Biology|Enhancer Elements, Genetic|Exons|Genes, Plant|RNA, Plant', 'Comparative Study', '10.1186/1471-2105-8-159', '17517127', 'Algorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.'),
(91492, 2007, 'bmc', 'TISs-ST: a web server to evaluate polymorphic translation initiation sites and their reflections on the secretory targets', 'Vicentini, Renato|Menossi, Marcelo', 'Functional Genomics Laboratory, Center for Molecular Biology and Genetic Engineering, State University of Campinas, Campinas, SP, Brazil. shinapes@unicamp.br <shinapes@unicamp.br>|Functional Genomics Laboratory, Center for Molecular Biology and Genetic Engineering, State University of Campinas, Campinas, SP, Brazil. shinapes@unicamp.br <shinapes@unicamp.br>', 'Brazil|Brazil', 0, 'Animals|Codon, Initiator|Databases, Nucleic Acid|Humans|Internet|Protein Biosynthesis|RNA, Messenger|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-160', '17517132', 'The nucleotide sequence flanking the translation initiation codon (start codon context) affects the translational efficiency of eukaryotic mRNAs, and may indicate the presence of an alternative translation initiation site (TIS) to produce proteins with different properties. Multi-targeting may reflect the translational variability of these other protein forms. In this paper we present a web server that performs computations to investigate the usage of alternative translation initiation sites for the synthesis of new protein variants that might have different functions.'),
(91493, 2007, 'bmc', 'Large-scale clustering of CAGE tag expression data', 'Shimokawa, Kazuro|Okamura-Oho, Yuko|Kurita, Takio|Frith, Martin C|Kawai, Jun|Carninci, Piero|Hayashizaki, Yoshihide', 'Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp|Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan. kazsi@gsc.riken.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 5, 'Algorithms|Animals|Chromosome Mapping|Expressed Sequence Tags|Gene Expression Profiling|Mice|Multigene Family|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-8-161', '17517134', 'Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. We have identified a huge number of TSSs mapped onto the mouse genome using the cap analysis of gene expression (CAGE) method. The standard hierarchical clustering algorithm, which gives us easily understandable graphical tree images, has difficulties in processing such huge amounts of TSS data and a better method to calculate and display the results is needed.'),
(91494, 2007, 'bmc', 'Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors', 'Kose, Frank|Budczies, Jan|Holschneider, Matthias|Fiehn, Oliver', 'Universitaet Potsdam, Potsdam, Germany. kose@likelynet.de <kose@likelynet.de>|Universitaet Potsdam, Potsdam, Germany. kose@likelynet.de <kose@likelynet.de>|Universitaet Potsdam, Potsdam, Germany. kose@likelynet.de <kose@likelynet.de>|Universitaet Potsdam, Potsdam, Germany. kose@likelynet.de <kose@likelynet.de>', 'Germany|Germany|Germany|Germany', 6, 'Algorithms|Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Linear Models|Models, Genetic|Models, Statistical|Proteome|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction', 'Evaluation Studies', '10.1186/1471-2105-8-162', '17517139', 'The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A tight control over metabolite ratios will be reflected by a linear relationship of pairs of metabolite due to the flexibility of metabolic pathways. Hence, unbiased detection and validation of linear metabolic variance can be interpreted in terms of biological control. For robust analyses, criteria for rejecting or accepting linearities need to be developed despite technical measurement errors. The entirety of all pair wise linear metabolic relationships then yields insights into the network of cellular regulation.'),
(91495, 2007, 'bmc', 'AT excursion: a new approach to predict replication origins in viral genomes by locating AT-rich regions', 'Chew, David S H|Leung, Ming-Ying|Choi, Kwok Pui', 'Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore. david.chew@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore. david.chew@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore. david.chew@nus.edu.sg', 'Singapore|Singapore|Singapore', 0, 'AT Rich Sequence|Algorithms|Base Sequence|Chromosome Mapping|Genome, Viral|Herpesviridae|Molecular Sequence Data|Replication Origin|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-163', '17517140', 'Replication origins are considered important sites for understanding the molecular mechanisms involved in DNA replication. Many computational methods have been developed for predicting their locations in archaeal, bacterial and eukaryotic genomes. However, a prediction method designed for a particular kind of genomes might not work well for another. In this paper, we propose the AT excursion method, which is a score-based approach, to quantify local AT abundance in genomic sequences and use the identified high scoring segments for predicting replication origins. This method has the advantages of requiring no preset window size and having rigorous criteria to evaluate statistical significance of high scoring segments.'),
(91496, 2007, 'bmc', 'Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis', 'Liu, Chun-Chi|Lin, Chin-Chung|Li, Ker-Chau|Chen, Wen-Shyen E|Chen, Jiun-Ching|Yang, Ming-Te|Yang, Pan-Chyr|Chang, Pei-Chun|Chen, Jeremy J W', 'Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>|Department of Computer Science, National Chung-Hsing University, Taichung, Taiwan, ROC. jjliu@cs.nchu.edu.tw <jjliu@cs.nchu.edu.tw>', '-|-|-|-|-|-|-|-|-', 5, 'Animals|Computational Biology|Genome|Genome, Human|Genomics|Humans|Neural Networks (Computer)|Oligonucleotides|Rats', 'Comparative Study', '10.1186/1471-2105-8-164', '17518996', 'Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.'),
(91497, 2007, 'bmc', 'Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue', 'Strickert, Marc|Sreenivasulu, Nese|Usadel, Björn|Seiffert, Udo', 'Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. stricker@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. stricker@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. stricker@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. stricker@ipk-gatersleben.de', 'Germany|Germany|Germany|Germany', 10, 'Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Developmental|Gene Expression Regulation, Plant|Hordeum|Oligonucleotide Array Sequence Analysis|Plant Proteins|Seeds', 'Journal Article', '10.1186/1471-2105-8-165', '17519012', 'Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper insights into regulatory behavior and cellular responses, as will be discussed for expression data of developing barley endosperm tissue. For that purpose, high-throughput multidimensional scaling (HiT-MDS), a recent method for similarity-preserving data embedding, is substantially refined and used for (a) assessing the quality and reliability of centroid gene expression patterns, and for (b) derivation of functional relationships of coexpressed genes of endosperm tissue during barley grain development (0-26 days after flowering).'),
(91498, 2007, 'bmc', 'GOSim--an R-package for computation of information theoretic GO similarities between terms and gene products', 'Fröhlich, Holger|Speer, Nora|Poustka, Annemarie|Beissbarth, Tim', 'German Cancer Research Center (DKFZ), Div. Molecular Genome Analysis, Im Neuenheimer Feld 580, Heidelberg, Germany. h.froehlich@dkfz.de|German Cancer Research Center (DKFZ), Div. Molecular Genome Analysis, Im Neuenheimer Feld 580, Heidelberg, Germany. h.froehlich@dkfz.de|German Cancer Research Center (DKFZ), Div. Molecular Genome Analysis, Im Neuenheimer Feld 580, Heidelberg, Germany. h.froehlich@dkfz.de|German Cancer Research Center (DKFZ), Div. Molecular Genome Analysis, Im Neuenheimer Feld 580, Heidelberg, Germany. h.froehlich@dkfz.de', 'Germany|Germany|Germany|Germany', 132, 'Base Sequence|Data Interpretation, Statistical|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Data|Programming Languages|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-166', '17519018', 'With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the analysis of such data often there is the need to further explore the similarity of genes not only with respect to their expression, but also with respect to their functional annotation which can be obtained from Gene Ontology (GO).'),
(91499, 2007, 'bmc', 'Hinge Atlas: relating protein sequence to sites of structural flexibility', 'Flores, Samuel C|Lu, Long J|Yang, Julie|Carriero, Nicholas|Gerstein, Mark B', 'Department of Physics, Yale University, New Haven, CT, USA. samuel.flores@yale.edu <samuel.flores@yale.edu>|Department of Physics, Yale University, New Haven, CT, USA. samuel.flores@yale.edu <samuel.flores@yale.edu>|Department of Physics, Yale University, New Haven, CT, USA. samuel.flores@yale.edu <samuel.flores@yale.edu>|Department of Physics, Yale University, New Haven, CT, USA. samuel.flores@yale.edu <samuel.flores@yale.edu>|Department of Physics, Yale University, New Haven, CT, USA. samuel.flores@yale.edu <samuel.flores@yale.edu>', 'United States|United States|United States|United States|United States', 33, 'Algorithms|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-8-167', '17519025', 'Relating features of protein sequences to structural hinges is important for identifying domain boundaries, understanding structure-function relationships, and designing flexibility into proteins. Efforts in this field have been hampered by the lack of a proper dataset for studying characteristics of hinges.'),
(91500, 2007, 'bmc', 'BioPP: a tool for web-publication of biological networks', 'Viswanathan, Ganesh A|Nudelman, German|Patil, Sonali|Sealfon, Stuart C', 'Center for Translational Systems Biology and Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA. ganesh.viswanathan@mssm.edu <ganesh.viswanathan@mssm.edu>|Center for Translational Systems Biology and Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA. ganesh.viswanathan@mssm.edu <ganesh.viswanathan@mssm.edu>|Center for Translational Systems Biology and Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA. ganesh.viswanathan@mssm.edu <ganesh.viswanathan@mssm.edu>|Center for Translational Systems Biology and Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA. ganesh.viswanathan@mssm.edu <ganesh.viswanathan@mssm.edu>', 'United States|United States|United States|United States', 13, 'Databases, Factual|Gene Regulatory Networks|Internet|Metabolic Networks and Pathways|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-8-168', '17519033', 'Cellular processes depend on the function of intracellular molecular networks. The curation of the literature relevant to specific biological pathways is important for many theoretical and experimental research teams and communities. No current tool supports web publication or hosting of user-developed large scale annotated pathway diagrams. Sharing via web publication is needed to allow real-time access to the current literature pathway knowledge-base, both privately within a research team or publicly among the outside research community. Web publication also facilitates team and/or community input into the curation process while allowing centralized control of the curation and validation process. We have developed new tool to address these needs. Biological Pathway Publisher (BioPP) is a software suite for converting CellDesigner Systems Biology Markup Language (CD-SBML) formatted pathways into a web viewable format. The BioPP suite is available for private use and for depositing knowledge-bases into a newly created public repository.'),
(91501, 2007, 'bmc', 'A feature selection approach for identification of signature genes from SAGE data', 'Barrera, Junior|Cesar, Roberto M|Humes, Carlos|Martins, David C|Patrão, Diogo F C|Silva, Paulo J S|Brentani, Helena', 'Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br|Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil. jb@ime.usp.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 4, 'Astrocytoma|Brain|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Library|Glioblastoma|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-169', '17519038', 'One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements.'),
(91502, 2007, 'bmc', 'Estimating the annotation error rate of curated GO database sequence annotations', 'Jones, Craig E|Brown, Alfred L|Baumann, Ute', 'School of Computer Science, University of Adelaide, South Australia, Australia. craig@cs.adelaide.edu.au|School of Computer Science, University of Adelaide, South Australia, Australia. craig@cs.adelaide.edu.au|School of Computer Science, University of Adelaide, South Australia, Australia. craig@cs.adelaide.edu.au', 'Australia|Australia|Australia', 97, 'Base Sequence|Data Interpretation, Statistical|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-170', '17519041', 'Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences.'),
(91503, 2007, 'bmc', 'Comparing segmentations by applying randomization techniques', 'Haiminen, Niina|Mannila, Heikki|Terzi, Evimaria', 'HIIT Basic Research Unit, Department of Computer Science, University of Helsinki, Finland. haiminen@cs.helsinki.fi|HIIT Basic Research Unit, Department of Computer Science, University of Helsinki, Finland. haiminen@cs.helsinki.fi|HIIT Basic Research Unit, Department of Computer Science, University of Helsinki, Finland. haiminen@cs.helsinki.fi', 'Finland|Finland|Finland', 13, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-8-171', '17521423', 'There exist many segmentation techniques for genomic sequences, and the segmentations can also be based on many different biological features. We show how to evaluate and compare the quality of segmentations obtained by different techniques and alternative biological features.'),
(91504, 2007, 'bmc', 'The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats', 'Grissa, Ibtissem|Vergnaud, Gilles|Pourcel, Christine', 'Univ Paris-Sud, Institut de Génétique et Microbiologie, UMR 8621, Orsay, France. ibtissem.grissa@igmors.u-psud.fr <ibtissem.grissa@igmors.u-psud.fr>|Univ Paris-Sud, Institut de Génétique et Microbiologie, UMR 8621, Orsay, France. ibtissem.grissa@igmors.u-psud.fr <ibtissem.grissa@igmors.u-psud.fr>|Univ Paris-Sud, Institut de Génétique et Microbiologie, UMR 8621, Orsay, France. ibtissem.grissa@igmors.u-psud.fr <ibtissem.grissa@igmors.u-psud.fr>', 'France|France|France', 612, 'Algorithms|Chromosome Mapping|DNA, Intergenic|Database Management Systems|Databases, Genetic|Genome, Archaeal|Genome, Bacterial|Repetitive Sequences, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-172', '17521438', 'In Archeae and Bacteria, the repeated elements called CRISPRs for clustered regularly interspaced short palindromic repeats are believed to participate in the defence against viruses. Short sequences called spacers are stored in-between repeated elements. In the current model, motifs comprising spacers and repeats may target an invading DNA and lead to its degradation through a proposed mechanism similar to RNA interference. Analysis of intra-species polymorphism shows that new motifs (one spacer and one repeated element) are added in a polarised fashion. Although their principal characteristics have been described, a lot remains to be discovered on the way CRISPRs are created and evolve. As new genome sequences become available it appears necessary to develop automated scanning tools to make available CRISPRs related information and to facilitate additional investigations.'),
(91505, 2007, 'bmc', 'Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment', 'Jothi, Raja|Przytycka, Teresa M|Aravind, L', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. jothi@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. jothi@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. jothi@ncbi.nlm.nih.gov', 'United States|United States|United States', 69, 'Chromosome Mapping|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Linkage Disequilibrium|Models, Biological|Phylogeny|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, DNA|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-173', '17521444', 'A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution.'),
(91506, 2007, 'bmc', 'Identification of candidate regulatory sequences in mammalian 3 UTRs by statistical analysis of oligonucleotide distributions', 'Corà, Davide|Di Cunto, Ferdinando|Caselle, Michele|Provero, Paolo', 'Dept of Theoretical Physics, University of Turin and INFN, Turin, Italy. cora@to.infn.it <cora@to.infn.it>|Dept of Theoretical Physics, University of Turin and INFN, Turin, Italy. cora@to.infn.it <cora@to.infn.it>|Dept of Theoretical Physics, University of Turin and INFN, Turin, Italy. cora@to.infn.it <cora@to.infn.it>|Dept of Theoretical Physics, University of Turin and INFN, Turin, Italy. cora@to.infn.it <cora@to.infn.it>', 'Italy|Italy|Italy|Italy', 13, '3 Untranslated Regions|Algorithms|Base Sequence|Data Interpretation, Statistical|MicroRNAs|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligonucleotides|Regulatory Elements, Transcriptional|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-8-174', '17524134', '3 untranslated regions (3 UTRs) contain binding sites for many regulatory elements, and in particular for microRNAs (miRNAs). The importance of miRNA-mediated post-transcriptional regulation has become increasingly clear in the last few years.');
