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	Modular analysis of the probabilistic genetic interaction network
	Hou, Lin ; Wang, Lin ; Qian, Minping ; Li, Dong ; Tang, Chao ; Zhu, Yunping ; Deng, Minghua ; Li, Fangting
	2011
关键词	SACCHAROMYCES-CEREVISIAE PROTEIN-INTERACTION FUNCTIONAL MODULES INTERACTION MAP YEAST COMPLEXES ORGANIZATION PHOSPHATASE BIOLOGY
英文摘要	Motivation: Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks; however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network. Results: Mixture modeling has been demonstrated as an effective soft-threshold technique of EMAP measures. The Bayesian approach was applied to an EMAP dataset studying the early secretory pathway in Saccharomyces cerevisiae. Twenty-seven modules were identified, and 14 of those were enriched by gold standard functional gene sets. We also conducted a detailed comparison with state-of-the-art algorithms, hierarchical cluster and Markov clustering. The experimental results show that the Bayesian approach outperforms others in efficiently recovering biologically significant modules. Contact: dengmh@pku.edu.cn; fangtingli@pku.edu.cn; zhuyp@hupo.org.cn Supplementary Information: Supplementary data are available at Bioinformatics online.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000288277300016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability; SCI(E); PubMed; 4; ARTICLE; 6; 853-859; 27
语种	英语
出处	PubMed ; SCI
出版者	bioinformatics
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/314178]
专题	数学科学学院 物理学院
推荐引用方式 GB/T 7714	Hou, Lin,Wang, Lin,Qian, Minping,et al. Modular analysis of the probabilistic genetic interaction network. 2011-01-01.

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