title: Inferring transcriptional interactions and regulator activities from experimental data.
abstract: Gene regulation is a fundamental process in biological systems, where transcription factors (TFs) play crucial roles. Inferring transcriptional interactions between TFs and their target genes has utmost importance for understanding the complex regulatory mechanisms in cellular systems. On one hand, with the rapid progress of various high-throughput experiment techniques, more and more biological data become available, which makes it possible to quantitatively study gene regulation in a systematic manner. On the other hand, transcription regulation is a complex biological process mediated by many events such as post-translational modifications, degradation, and competitive binding of multiple TFs. In this review, with a particular emphasis on computational methods, we report the recent advances of the research topics related to transcriptional regulatory networks, including how to infer transcriptional interactions, reveal combinatorial regulation mechanisms, and reconstruct TF activity profiles.
authors.affiliation: Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, Osaka 574-8530, Japan.
authors.forename: Rui-Sheng
authors.initials: RS
authors.lastname: Wang
authors.forename: Xiang-Sun
authors.initials: XS
authors.lastname: Zhang
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000502:physiology*; D008957:Models, Genetic; D014157:Transcription Factors / Q000502:physiology*; D014158:Transcription, Genetic / Q000502:physiology*
chemical_list: D014157:Transcription Factors