Summary
the 2014 International Symposium on Nonlinear Theory and its Applications
2014
Session Number:D2L-D
Session:
Number:D2L-D3
Filter-based Robustness Analysis of Cellular Signaling Pathways Considering Flow Dynamics
Jian-Qin Liu,
pp.795-798
Publication Date:2014/9/14
Online ISSN:2188-5079
Summary:
Traditional studies on the dynamics of cellular signal transmission are mainly limited to the applications of feedback control models where factors affecting the molecular signal flow, which implies the flow of molecular signals in terms of molecular concentration that expresses "information" of the dynamics of cellular functions, are not considered. But reported evidence on cellular signal transmission indicates that the accuracy and efficiency of the flow of molecular signals determines the activation of cellular signaling pathways, which is closely related to the fate of the cell. The feedback control model without considering the inevitable factor ? the dynamics of the flow in signal transmission, cannot well explain the phenomenon of the feedback enhancement on the flow of molecular signals in signaling pathway networks. In this paper, a new filter-based method called the network filter in which the non-smooth state transition caused by the signal transmission in different steady states of the feedback controller is detected by a filtering mechanism that characterizes the statistical feature of molecular information channel to perform the quantitative robustness analysis of the heat shock response (HSR) network of E. coli is proposed. The simulation result of the robustness of the HSR network is verified by my software simulator of signal transmission processes in the cell by using a channel structure, which can quantitatively describe the characteristics of the molecular signal flow to formulate the cellular signal transmission process. The dynamics of the flow that characterizes the signal transmission process has been proven to be an adequate measurable criterion to testify the effect of feedback on robustness of signal transduction in protein folding. The results obtained demonstrate that the flow dynamics in the HSR network obeys the constructal law, which not only shows the feasibility of this method for the identification of the parameters that characterize the flow in robust cellular signaling pathway networks to find the crucial factors that affect the robustness of HSP but also shows the possibility of being used as a theoretical tool for the analysis of a broad class of dynamic networks in general because HSP determines the protein folding and the failure of the protein folding may cause neuro-degeneration.