Work

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation

Year: 2016

Type: article

Abstract: BACKGROUND: Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. METHODS: A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. RESULTS: Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. CONCLUSIONS: As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. AVAILABILITY: http://histone.scse.ntu.edu.sg/Sig2GRN/.

Source: BMC Systems Biology

DOI: 10.1186/s12918-016-0365-1

Authors: Fan Zhang, Runsheng Liu, Jie Zheng

Institutions: Nanyang Technological University, Agency for Science, Technology and Research, Genome Institute of Singapore

Language: English

Topic: Gene Regulatory Network Analysis

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,290

Funders: Ministry of Education - Singapore, Nanyang Technological University, Ministry of Education, India