Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/80431
Title: Sig2GRN : a software tool linking signaling pathway with gene regulatory network for dynamic simulation
Authors: Zhang, Fan
Liu, Runsheng
Zheng, Jie
Keywords: Transcription Factor Activity
Gene Regulatory Network
DRNTU::Engineering::Computer science and engineering
Issue Date: 2016
Source: Zhang, F., Liu, R., & Zheng, J. (2016). Sig2GRN : a software tool linking signaling pathway with gene regulatory network for dynamic simulation. BMC Systems Biology, 10(S4), 123-. doi:10.1186/s12918-016-0365-1
Series/Report no.: BMC Systems Biology
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.
URI: https://hdl.handle.net/10356/80431
http://hdl.handle.net/10220/46551
DOI: 10.1186/s12918-016-0365-1
DOI (Related Dataset): https://doi.org/10.21979/N9/SO9VRB
Rights: © 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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