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检索条件"任意字段=2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005"

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Proceedings of the 2005 ieee computational systems bioinformatics conference Workshops(csbW'05)

Proceedings of the 2005 IEEE Computational Systems Bioinform...

引用

2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

ISBN: (纸本)0769524427

The proceedings contain 127 papers. The topics discussed include: sequential classification for microarray and clinical data;efficient image texture analysis and classification for prostate ultrasound diagnosis;diagnosis and biomarker identification on SELDI proteomics data by ADTboost;inverse design of large molecules using linear Diophantine equations;reducing gene regulatory networks by decomposition;a diffusion model to estimate the inter-arrival time of charged molecules in stochastic event based modeling of complex biological networks;operon prediction in cyanobacteria using comparative genomics;patterns of gene deletion following genome duplication in yeast;classification methods for HIV-1 medicated neuronal damage;key features of the UCSC genome site;data integration in the Mouse Genome Informatics (MGI) database;HIV structural and biothermodynamics databases: A resource for the pharmaceutical and biotechnology industry;a new clustering strategy with stochastic merging and removing based on kernel functions;head and neck cancer metastasis prediction via artificial neural networks;and problem solving environment approach to integrating diverse biological data sources.

关键词： Biotechnology

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Gene Networks Inference From Expression Data Using a Recurrent Neuro-Fuzzy Approach

Gene Networks Inference From Expression Data Using a Recurre...

引用

Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： I. Maraziotis A. Dragomir A. Bezerianos Department of Medical Physics University of Patras Rio Greece

The reverse engineering paradigm is given increasing attention in computational molecular biology lately. One of the goals is to understand how gene regulatory networks (complex systems of genes, proteins and other molecules) function and interact to carry out specific cell functions. We present an approach for inferring the complex causal relationships among genes from microarray experimental data based on a recurrent neuro-fuzzy method. The method derives information on the gene interactions in a highly interpretable form (fuzzy rules) and takes into account dynamical aspects of genes regulation through its recurrent structure. We tested our approach on a set of genes known to be highly regulated during the yeast cell-cycle. The retrieved gene interactions correspond to the ones validated by previous biological studies, while our method surpasses previous computational techniques that attempted gene networks reconstruction, being able to retrieve significantly more biologically valid relationships among genes. At the same time, our method is able to predict time series for the expression of the genes based on the information extracted from a training subset of the data. The results prove highly accurate prediction capability

关键词： Computer networks Gene expression Fuzzy systems Reverse engineering Biology computing Data mining Data analysis Biological system modeling Genomics bioinformatics

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The Cancer Biomedical Informatics Grid (caBIGTM)

The Cancer Biomedical Informatics Grid (caBIGTM)

引用

Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： D. Fenstermacher C. Street T. McSherry V. Nayak C. Overby M. Feldman Department of Pathology and Laboratory Medicine University of Pennsylvania USA Biomedical Informatics Facility Abramson Cancer Center University of Pennsylvania USA

The Cancer Biomedical Informatics Grid (caBIGtrade) is a new project initiated by the National Cancer Institute to create a computational network connecting scientists and institutions to enable the sharing of data and the use of common analytical tools. The emergence of genomics and proteomics high-throughput technologies are creating a paradigm shift in biomedical research from small independent labs to large teams of researchers exploring entire genomes and proteomes and how they relate to disease. caBIGtrade is developing new software and modifying existing software within Clinical Trials Management systems, Tissue Banks and Pathology Tools and Integrated Cancer Research tools to manage the huge volume of data being generated and to facilitate collaboration across the broad spectrum of cancer research

关键词： Cancer Biomedical informatics Collaborative software Genomics bioinformatics Software tools Software development management Technology management Biomedical computing Computer networks

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Assessing the Codetermination of Gene Transcriptional States Using Both Superscalar and Vector Multiple Processor systems

Assessing the Codetermination of Gene Transcriptional States...

引用

Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： R.L. Martino D.E. Russ C.A. Johnson Division of Computational Bioscience Center for Information TechnologyDepartment of Health and Human Services National Institutes of Health DHHS Bethesda MD USA

An important goal of functional genomics is to develop methods for determining ways in which individual actions of genes are integrated in the cell. One way of gaining insight into a gene's role in cellular activity is to study its expression pattern in a variety of circumstances and contexts, as it responds to its environment and to the action of other genes. Microarrays provide large-scale surveys of gene expression in which transcript levels can be determined for thousands of genes simultaneously. The coefficient of determination (CoD) has been proposed for the analysis of gene interaction via multivariate expression arrays. Parallel computing is essential to the application of the CoD to a large set of genes because of the large number of expression-based functions that must be statistically designed and compared. The results of the calculation of the CoD for a large set of genes with multiple superscalar processors are presented. A proposal for calculating the CoD with multiple vector processors is described. Multiple vector processor systems offer the potential to greatly reduce the time to calculate the CoD for a large set of genes

关键词： Gene expression DNA Genomics bioinformatics Large-scale systems Parallel processing Vector processors Biological information theory Information technology Humans

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The center for computational biology

The center for computational biology

引用

ieee computational systems bioinformatics conference

作者： Toga, AW Univ Calif Los Angeles Sch Med Lab Neuro Imaging Los Angeles CA 90024 USA

not avaliable

ISBN: (纸本)0769523447

not avaliable

关键词： computational Biology bioinformatics

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Bioinformatic insights from metagenomics through visualization

Bioinformatic insights from metagenomics through visualizati...

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ieee computational systems bioinformatics conference

作者： Havre, SL Webb-Robertson, BJ Shah, A Posse, C Gopalan, B Brockman, FJ Pacific NW Natl Lab Richland WA 99352 USA

ISBN: (纸本)0769523447

Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily, discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by, algorithms, may, reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.

关键词： bioinformatics visualization metagenomics categorical nominal

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Gene teams with relaxed proximity constraint

Gene teams with relaxed proximity constraint

引用

2005 ieee computational systems bioinformatics conference, csb 2005

作者： Kim, Sun Choi, Jeong-Hyeon Yang, Jiong School of Informatics Center for Genomics and Bioinformatics Indiana University IN 47408 United States School of Informatics Indiana University IN 47408 United States EECS Case Western Reserve Univ. OH 44106 United States

ISBN: (纸本)0769523447

Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity among genes, known as gene team, is a very useful concept to discover functionally related genes in multiple genomes. However, there are also many gene sets that do not preserve physical proximity. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraint. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. Especially, analysis of gene clusters that belong to B. subtilis and E. coli demonstrated that our model predicted many experimentally verified operons and functionally related clusters. Our program is fast enough to provide a sevice on the web at http://***/platcom/. Users can select any combination of 97 genomes to predict gene teams. © 2005 ieee.

关键词： Genes

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PLATCOM: A platform for computational comparative genomics on the Web

PLATCOM: A platform for computational comparative genomics o...

引用

2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Choi, Kwangmin Choi, Jeong-Hyeon Saple, Amit Wang, Zhiping Lee, Jason Kim, Sun School of Informatics Center for Genomics and Bioinformatics Indiana University IN 47408 United States

No abstract available

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Key features of the UCSC genome site

Key features of the UCSC genome site

引用

2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Trumbower, Heather Jackson, Jennifer UCSC Genome Bioinformatics Group

ISBN: (纸本)0769524427

关键词： Genetic engineering

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Cluster utility: A new metric for clustering biological sequences

Cluster utility: A new metric for clustering biological sequ...

引用

2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Lee, Jason Kim, Sun School of Informatics Indiana University Bloomington IN 47404 United States Center for Genomics and Bioinformatics Indiana University Bloomington IN 47404 United States

No abstract available

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