摘要翻译:
Asterias(\URL{http://www.Asterias.info})是用于分析基因表达和aCGH数据的可免费访问的web工具的集成集合。大多数工具使用并行计算(通过MPI)。我们的大多数应用程序允许用户通过使用表格和/或图形中的可点击链接来获得用户选择的基因的额外信息。我们的工具包括:表达和aCGH数据的规范化;不同类型的基因/克隆和蛋白质标识符之间的转换;过滤和归责;寻找与患者类别和生存数据相关的差异表达基因;寻找类预测模型;利用随机森林搜索类预测的最小模型或具有预测能力的大基因子集;用生存数据寻找分子签名和预测基因;检测基因组DNA获得或丢失的区域。在不同的应用程序之间发送结果、访问附加功能信息和并行化计算的能力使我们的套件具有独特性,并利用了仅可用于基于Web的应用程序的特性。
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英文标题:
《Asterias: a parallelized web-based suite for the analysis of expression
and aCGH data》
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作者:
Andreu Alibes, Edward R. Morrissey, Andres Canada, Oscar M. Rueda,
David Casado, Patricio Yankilevich, Ramon Diaz-Uriarte
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最新提交年份:
2006
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分类信息:
一级分类:Quantitative Biology 数量生物学
二级分类:Genomics 基因组学
分类描述:DNA sequencing and assembly; gene and motif finding; RNA editing and alternative splicing; genomic structure and processes (replication, transcription, methylation, etc); mutational processes.
DNA测序与组装;基因和基序的发现;RNA编辑和选择性剪接;基因组结构和过程(复制、转录、甲基化等);突变过程。
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一级分类:Quantitative Biology 数量生物学
二级分类:Other Quantitative Biology 其他定量生物学
分类描述:Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要:
Asterias (\url{http://www.asterias.info}) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI). Most of our applications allow the user to obtain additional information for user-selected genes by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data; converting between different types of gene/clone and protein identifiers; filtering and imputation; finding differentially expressed genes related to patient class and survival data; searching for models of class prediction; using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity; searching for molecular signatures and predictive genes with survival data; detecting regions of genomic DNA gain or loss. The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications.
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PDF链接:
https://arxiv.org/pdf/q-bio/0610039