An integrative method to decode regulatory logics in gene transcription

Bin Yan, Daogang Guan, Chao Wang, Junwen Wang, Bing He, Jing Qin, Kenneth R. Boheler, Aiping Lu, Ge Zhang, Hailong Zhu

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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 studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.

Original languageEnglish (US)
Article number1044
JournalNature communications
Issue number1
StatePublished - Dec 1 2017

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • General
  • Physics and Astronomy(all)


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