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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing
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Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing

机译：使用高性能计算从基因表达谱进行全基因组基因调控网络的逆向工程和分析

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摘要

Regulation of gene expression is a carefully regulated phenomenon in the cell. "Reverse-engineeringȁD; algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover "communitiesȁD; within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.
机译：基因表达的调节是细胞中一种精心调节的现象。 “逆向工程学；算法试图通过基因表达谱（微阵列）的基因组规模测量来重建基因之间的调控相互作用。哺乳动物细胞表达成千上万个基因；因此，数百个基因表达谱是必需的，以使其具有可接受性。基因之间相互作用的统计证据。随着要分析的谱图数量的增加，计算成本和内存需求也随之增加。在这项工作中，我们设计和开发了一种并行计算算法，可以逆向工程化成千上万的基因组规模的基因调控网络。基因表达谱。该算法基于计算每个基因对之间的成对相互信息。我们成功地对其进行了测试，以便根据从公共资源库收集的基因表达谱对肝脏中的Mus Musculus（小鼠）基因调控网络进行反向工程。实施聚类算法以发现“社区comD”。基因网络中。网络社区丰富了涉及相同生物学功能的基因。推断的网络用于鉴定两种线粒体蛋白。

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