Method for inferring and extracting reliable genetic interactions from time-series profile of gene expression
Method for inferring and extracting reliable genetic interactions from time-series profile of gene expression
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DOI：
10.1016/j.mbs.2008.06.007
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发表时间：
2008-09-01
影响因子：
4.3
通讯作者：
Okamoto, Masahiro
中科院分区：
文献类型：
--
作者：
Nakatsui, Masahiko;Ueda, Takanori;Okamoto, Masahiro
DNA微阵列等技术的最新进展提供了丰富的基因组规模的基因表达数据。后基因组时代最重要的研究课题之一是基因表达网络的系统识别。然而，从实验观察到的色调系列数据推断内部基因表达结构是一个逆问题。因此，我们开发了一个系统，用于根据实验观察推断网络候选人。此外，我们提出了一种分析方法，从各种网络候选人提取共同的核心二项式遗传相互作用。共同核心二项遗传相互作用是存在可能性较高的可靠相互作用，对于理解基因表达网络的动态行为非常重要。在这里，我们讨论了一种有效的方法来推断遗传相互作用，结合一步一步的战略（Y。Maki，Y.高桥，Y. Arikawa，S.渡边K. Aoshima，Y. Eguchi，T.上田，S. Aburatani，S. Kuhara，M. Okamoto，An integrated comprehensive workbench for inferred genetic networks：Voyagene，Journal of Bioinformatics and Computational Biology 2（3）（2004）533.）用分析方法提取共同核心二项遗传互作。(c)2008年爱思唯尔公司All rights reserved.
Recent advances in technologies such as DNA microarrays have provided an abundance of gene expression data on the genomic scale. One of the most important projects in the post-genome-era is the systemic identification of gene expression networks. However, inferring internal gene expression structure from experimentally observed tinge-series data are an inverse problem. We have therefore developed a system for inferring network candidates based on experimental observations. Moreover, we have proposed an analytical method for extracting common core binomial genetic interactions from various network candidates. Common core binomial genetic interactions are reliable interactions with a higher possibility of existence, and are important for Understanding the dynamic behavior of gene expression networks. Here, we discuss an efficient method for inferring genetic interactions that combines a Step-by-step strategy (Y. Maki, Y. Takahashi, Y. Arikawa, S. Watanabe, K. Aoshima, Y. Eguchi, T. Ueda, S. Aburatani, S. Kuhara, M. Okamoto, An integrated comprehensive workbench for inferring genetic networks: Voyagene, Journal of Bioinformatics and Computational Biology 2(3) (2004) 533.) with an analysis method for extracting common core binomial genetic interactions. (c) 2008 Elsevier Inc. All rights reserved.