Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11538-012-9733-1
Title: Modeling of Hysteresis in Gene Regulatory Networks
Authors: Hu, J.
Qin, K.R.
Xiang, C. 
Lee, T.H. 
Keywords: BIBO stability
Gene regulatory network
Hysteresis
Modified Bouc-Wen model
Positive Feedback
Transient response
Issue Date: Aug-2012
Source: Hu, J., Qin, K.R., Xiang, C., Lee, T.H. (2012-08). Modeling of Hysteresis in Gene Regulatory Networks. Bulletin of Mathematical Biology 74 (8) : 1727-1753. ScholarBank@NUS Repository. https://doi.org/10.1007/s11538-012-9733-1
Abstract: Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E. coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function. © 2012 Society for Mathematical Biology.
Source Title: Bulletin of Mathematical Biology
URI: http://scholarbank.nus.edu.sg/handle/10635/50980
ISSN: 00928240
DOI: 10.1007/s11538-012-9733-1
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