Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation
Fan Zhang1, Runsheng Liu1, Jie Zheng2,3,4
1School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
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/.
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