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Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach
Ye, Yusen1; Gao, Lin1; Zhang, Shihua2,3
2017-09-28
Source PublicationFRONTIERS IN GENETICS
ISSN1664-8021
Volume8Pages:12
AbstractTranscription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.
Keywordtranscription regulation TF regulatory networks tensor factorization integrative analysis of omics data biological networks
DOI10.3389/fgene.2017.00140
Language英语
Funding ProjectNational Center for Mathematics and Interdisciplinary Sciences ; Academy of Mathematics and Systems Science ; CAS ; National Natural Science Foundation of China[61532014] ; National Natural Science Foundation of China[91530113] ; National Natural Science Foundation of China[61432010] ; National Natural Science Foundation of China[61621003] ; National Natural Science Foundation of China[61422309] ; National Natural Science Foundation of China[61379092] ; National Natural Science Foundation of China[11661141019] ; Chinese Academy of Sciences (CAS)[XDB13040600] ; CAS Frontier Science Research Key Project[QYZDB-SSW-SYS0080] ; Key Laboratory of Random Complex Structures and Data Science at CAS ; Fundamental Research Funds for the Central Universities[BDZ021404]
WOS Research AreaGenetics & Heredity
WOS SubjectGenetics & Heredity
WOS IDWOS:000412012200001
PublisherFRONTIERS MEDIA SA
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/26700
Collection应用数学研究所
Affiliation1.Xidian Univ, Sch Comp Sci & Technol, Xian, Shaanxi, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, RCSDS, NCMIS,CEMS, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Ye, Yusen,Gao, Lin,Zhang, Shihua. Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach[J]. FRONTIERS IN GENETICS,2017,8:12.
APA Ye, Yusen,Gao, Lin,&Zhang, Shihua.(2017).Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.FRONTIERS IN GENETICS,8,12.
MLA Ye, Yusen,et al."Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach".FRONTIERS IN GENETICS 8(2017):12.
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