PTHGRN: Unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data

Daogang Guan, Jiaofang Shao, Zhongying Zhao, Panwen Wang, Jing Qin, Youping Deng, Kenneth R. Boheler*, Junwen Wang*, Bin Yan*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

28 Citations (Scopus)


Interactions among transcriptional factors (TFs), cofactors and other proteins or enzymes can affect transcriptional regulatory capabilities of eukaryotic organisms. Post-translational modifications (PTMs) cooperate with TFs and epigenetic alterations to constitute a hierarchical complexity in transcriptional gene regulation. While clearly implicated in biological processes, our understanding of these complex regulatory mechanisms is still limited and incomplete. Various online software have been proposed for uncovering transcriptional and epigenetic regulatory networks, however, there is a lack of effective web-based software capable of constructing underlying interactive organizations between post-translational and transcriptional regulatory components. Here, we present an open web server, post-translational hierarchical gene regulatory network (PTHGRN) to unravel relationships among PTMs, TFs, epigenetic modifications and gene expression. PTHGRN utilizes a graphical Gaussian model with partial least squares regression-based methodology, and is able to integrate protein-protein interactions, ChIP-seq and gene expression data and to capture essential regulation features behind high-throughput data. The server provides an integrative platform for users to analyze ready-to-use public high-throughput Omics resources or upload their own data for systems biology study. Users can choose various parameters in the method, build network topologies of interests and dissect their associations with biological functions. Application of the software to stem cell and breast cancer demonstrates that it is an effective tool for understanding regulatory mechanisms in biological complex systems. PTHGRN web server is publically available at web site

Original languageEnglish
Pages (from-to)W130-W136
Number of pages7
JournalNucleic Acids Research
Issue numberW1
Early online date29 May 2014
Publication statusPublished - 1 Jul 2014

Scopus Subject Areas

  • Genetics


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