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Issue No.03 - May-June (2013 vol.10)
pp: 771-779
Wei Zhang , Sch. of Math. & Stat., Wuhan Univ., Wuhan, China
Xiufen Zou , Sch. of Math. & Stat., Wuhan Univ., Wuhan, China
ABSTRACT
Based on biological experimental data, we developed a mathematical model of the virus-triggered signaling pathways that lead to induction of type I IFNs and systematically analyzed the mechanisms of the cellular antiviral innate immune responses, including the negative feedback regulation of ISG56 and the positive feedback regulation of IFNs. We found that the time between 5 and 48 hours after viral infection is vital for the control and/or elimination of the virus from the host cells and demonstrated that the ISG56-induced inhibition of MITA activation is stronger than the ISG56-induced inhibition of TBK1 activation. The global parameter sensitivity analysis suggests that the positive feedback regulation of IFNs is very important in the innate antiviral system. Furthermore, the robustness of the innate immune signaling network was demonstrated using a new robustness index. These results can help us understand the mechanisms of the virus-induced innate immune response at a system level and provide instruction for further biological experiments.
INDEX TERMS
Mathematical model, Negative feedback, Immune system, Analytical models, Sensitivity analysis, Proteins, Simulation,positive feedback, physiological models, cellular biophysics, microorganisms, time 5 hour to 48 hour, innate antiviral system, virus-induced innate immune response, innate immune signaling network, TBK1 activation, MITA activation, ISG56-induced inhibition, viral infection, cellular antiviral innate immune responses, mathematical model, biological experimental data, virus-triggered type I IFN signaling, Mathematical model, Negative feedback, Immune system, Analytical models, Sensitivity analysis, Proteins, Simulation, robustness, Signaling pathways, mathematical modeling, negative feedback
CITATION
Wei Zhang, Xiufen Zou, "Systematic Analysis of the Mechanisms of Virus-Triggered Type I IFN Signaling Pathways through Mathematical Modeling", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.10, no. 3, pp. 771-779, May-June 2013, doi:10.1109/TCBB.2013.31
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