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System Identification Models for Gene Regulation System
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Recent bio-technologies enable us to successfully discover the functional organization of a cell by simultaneously measuring the dynamic change of concentrations of thousands of bio-molecules after specific perturbation。 Such available inputoutput data offer system identification great chances and meanwhile challenges to build mathematical models of the dynamic transcriptional control system， which is fundamentally important in systems biology。 Here， we propose a general mathematical framework to describe the real world of transcriptional control system and the related system identification problems。 Then some existing models are briefly introduced within this unified framework to infer gene regulatory networks or transcriptional regulatory network by incorporating prior information both on network structure and heterogeneous data sources。
WANG Yong、ZHANG Xiang-Sun、HORIMOTO Katsuhisa、CHEN Luonan
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Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, P. R. China
Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan
Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue-Yang Road, Shanghai 200031, P. R. China
Beijing(CN)
Proceedings of the 29th Chinese Control Conference
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