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An integrative method to decode regulatory logics in gene transcription

Abstract Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application ... (more)
Created Date 2017-10-19
Contributor Yan, Bin (Author) / Guan, Daogang (Author) / Wang, Chao (Author) / Wang, Junwen (ASU author) / He, Bing (Author) / Qin, Jing (Author) / Boheler, Kenneth R. (Author) / Lu, Aiping (Author) / Zhang, Ge (Author) / Zhu, Hailong (Author) / College of Health Solutions / Department of Biomedical Informatics
Type Text
Extent 12 pages
Language English
Identifier DOI: 10.1038/s41467-017-01193-0 / ISSN: 2041-1723
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Citation Yan, B., Guan, D., Wang, C., Wang, J., He, B., Qin, J., . . . Zhu, H. (2017). An integrative method to decode regulatory logics in gene transcription. Nature Communications, 8(1). doi:10.1038/s41467-017-01193-0
Note The final version of this article, as published in Nature Communications, can be viewed online at:
Collaborating Institutions ASU Library
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