Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data

doi:10.1093/nar/gkp625

CSpace > 应用数学研究所

	Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data
	Wang, Yong1,2 ; Zhang, Xiang-Sun2 ; Xia, Yu 1
	2009-10-01
发表期刊	NUCLEIC ACIDS RESEARCH
ISSN	0305-1048
卷号	37 期号:18 页码:5943-5958
摘要	Transcriptional cooperativity among several transcription factors (TFs) is believed to be the main mechanism of complexity and precision in transcriptional regulatory programs. Here, we present a Bayesian network framework to reconstruct a high-confidence whole-genome map of transcriptional cooperativity in Saccharomyces cerevisiae by integrating a comprehensive list of 15 genomic features. We design a Bayesian network structure to capture the dominant correlations among features and TF cooperativity, and introduce a supervised learning framework with a well-constructed gold-standard dataset. This framework allows us to assess the predictive power of each genomic feature, validate the superior performance of our Bayesian network compared to alternative methods, and integrate genomic features for optimal TF cooperativity prediction. Data integration reveals 159 high-confidence predicted cooperative relationships among 105 TFs, most of which are subsequently validated by literature search. The existing and predicted transcriptional cooperativities can be grouped into three categories based on the combination patterns of the genomic features, providing further biological insights into the different types of TF cooperativity. Our methodology is the first supervised learning approach for predicting transcriptional cooperativity, compares favorably to alternative unsupervised methodologies, and can be applied to other genomic data integration tasks where high-quality gold-standard positive data are scarce.
DOI	10.1093/nar/gkp625
语种	英语
资助项目	National Natural Science Foundation of China[10801131] ; National Natural Science Foundation of China[10631070] ; National Natural Science Foundation of China[60873205] ; Chinese Academy of Sciences[kjcs-yw-s7] ; National Basic Research Program[2006CB503900] ; PhRMA Foundation
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemistry & Molecular Biology
WOS记录号	WOS:000271109300008
出版者	OXFORD UNIV PRESS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/9232
专题	应用数学研究所
通讯作者	Xia, Yu
作者单位	1.Boston Univ, Dept Chem, Bioinformat Program, Boston, MA 02215 USA 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yong,Zhang, Xiang-Sun,Xia, Yu. Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data[J]. NUCLEIC ACIDS RESEARCH,2009,37(18):5943-5958.
APA	Wang, Yong,Zhang, Xiang-Sun,&Xia, Yu.(2009).Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data.NUCLEIC ACIDS RESEARCH,37(18),5943-5958.
MLA	Wang, Yong,et al."Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data".NUCLEIC ACIDS RESEARCH 37.18(2009):5943-5958.