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MODELING GENETIC REGULATORY NETWORKS: A DELAY DISCRETE DYNAMICAL MODEL APPROACH

Hao JIANG1 , Wai-Ki CHING1 , Kiyoko F2,AOKI-KINOSHITA2 , Dianjing GUO3   

  1. 1. Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong, China; 2. Department of Bioinformatics, Faculty of Engineering, Soka University, Tokyo, Japan; 3. Department of Biology, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
  • Received:2010-09-09 Online:2012-12-25 Published:2012-12-20
  • Supported by:

    ∗This Research was supported in part by HKRGC Grant, HKU Strategic Theme Grant on Computational Sciences, National Natural Science Foundation of China under Grant Nos. 10971075 and 11271144.

Hao JIANG , Wai-Ki CHING , Kiyoko F,AOKI-KINOSHITA , Dianjing GUO. MODELING GENETIC REGULATORY NETWORKS: A DELAY DISCRETE DYNAMICAL MODEL APPROACH[J]. Journal of Systems Science and Complexity, 2012, 25(6): 1052-1067.

Modeling genetic regulatory networks is an important research topic in genomic research and computational systems biology. This paper considers the problem of constructing a genetic regulatory network (GRN) using the discrete dynamic system (DDS) model approach. Although considerable research has been devoted to building GRNs, many of the works did not consider the time-delay effect. Here, the authors propose a time-delay DDS model composed of linear difference equations to represent temporal interactions among significantly expressed genes. The authors also introduce interpolation scheme and re-sampling method for equalizing the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed genetic network using linear multiple regression matches with the original data very well. Simulation results are given to demonstrate the effectiveness of the proposed method and model.
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