CSpace
Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data
Zamanighomi, Mahdi1; Lin, Zhixiang1; Wang, Yong2; Jiang, Rui3,4; Wong, Wing Hung1,5
2017-06-02
Source PublicationNUCLEIC ACIDS RESEARCH
ISSN0305-1048
Volume45Issue:10Pages:5666-5677
AbstractTranscription factors (TFs) play crucial roles in regulating gene expression through interactions with specific DNA sequences. Recently, the sequence motif of almost 400 human TFs have been identified using high-throughput SELEX sequencing. However, there remain a large number of TFs (similar to 800) with no high-throughput-derived binding motifs. Computational methods capable of associating known motifs to such TFs will avoid tremendous experimental efforts and enable deeper understanding of transcriptional regulatory functions. We present a method to associate known motifs to TFs (MATLAB code is available in Supplementary Materials). Our method is based on a probabilistic framework that not only exploits DNA-binding domains and specificities, but also integrates open chromatin, gene expression and genomic data to accurately infer monomeric and homodimeric binding motifs. Our analysis resulted in the assignment of motifs to 200 TFs with no SELEX-derived motifs, roughly a 50% increase compared to the existing coverage.
DOI10.1093/nar/gkx358
Language英语
Funding ProjectNational Institutes of Health (NIH)[R01HG007834] ; National Institutes of Health (NIH)[P50HG007735] ; NIH[R01HG007834]
WOS Research AreaBiochemistry & Molecular Biology
WOS SubjectBiochemistry & Molecular Biology
WOS IDWOS:000402510700021
PublisherOXFORD UNIV PRESS
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/25640
Collection中国科学院数学与系统科学研究院
Affiliation1.Stanford Univ, Dept Stat, Stanford, CA 94305 USA
2.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
3.Tsinghua Univ, TNLIST, Dept Automat, Bioinformat Div,MOE Key Lab Bioinformat, Beijing 100084, Peoples R China
4.Tsinghua Univ, Ctr Synthet & Syst Biol, Dept Automat, Beijing 100084, Peoples R China
5.Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA
Recommended Citation
GB/T 7714
Zamanighomi, Mahdi,Lin, Zhixiang,Wang, Yong,et al. Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data[J]. NUCLEIC ACIDS RESEARCH,2017,45(10):5666-5677.
APA Zamanighomi, Mahdi,Lin, Zhixiang,Wang, Yong,Jiang, Rui,&Wong, Wing Hung.(2017).Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data.NUCLEIC ACIDS RESEARCH,45(10),5666-5677.
MLA Zamanighomi, Mahdi,et al."Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data".NUCLEIC ACIDS RESEARCH 45.10(2017):5666-5677.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zamanighomi, Mahdi]'s Articles
[Lin, Zhixiang]'s Articles
[Wang, Yong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zamanighomi, Mahdi]'s Articles
[Lin, Zhixiang]'s Articles
[Wang, Yong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zamanighomi, Mahdi]'s Articles
[Lin, Zhixiang]'s Articles
[Wang, Yong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.