Computation Intelligent for Eukaryotic Cell-Cycle Gene Network

Computational intelligent approaches is adopted to construct the S-system of eukaryotic cell cycle for further analysis of genetic regulatory networks. A highly nonlinear power-law differential equation is constructed to describe the transcriptional regulation of gene network from the time-courses dataset. Global artificial algorithm, based on hybrid differential evolution, can achieve global optimization for the highly nonlinear differential gene network modeling. The constructed gene regulatory networks will be a reference for researchers to realize the inhibitory and activatory operator for genes synthesis and decomposition in Eukaryotic cell cycle

[1]  Shuhei Kimura,et al.  Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm , 2005, Bioinform..

[2]  Masaru Tomita,et al.  Dynamic modeling of genetic networks using genetic algorithm and S-system , 2003, Bioinform..

[3]  J. Tyson,et al.  Model scenarios for evolution of the eukaryotic cell cycle. , 1998, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[4]  Eberhard O. Voit,et al.  Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists , 2000 .

[5]  M. Savageau.  Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology , 1976 .

[6]  Hitoshi Iba,et al.  Evolutionary modeling and inference of gene network , 2002, Inf. Sci..

[7]  Feng-Sheng Wang,et al.  Evolutionary optimization with data collocation for reverse engineering of biological networks , 2005, Bioinform..

[8]  H. Iba,et al.  Inferring a system of differential equations for a gene regulatory network by using genetic programming , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[9]  Hitoshi Iba,et al.  Inference of gene regulatory networks using s-system and differential evolution , 2005, GECCO '05.

[10]  K Nasmyth,et al.  Evolution of the cell cycle. , 1995, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[11]  J. Tyson,et al.  Regulation of the eukaryotic cell cycle: molecular antagonism, hysteresis, and irreversible transitions. , 2001, Journal of theoretical biology.

[12]  Eberhard O Voit,et al.  Priming nonlinear searches for pathway identification , 2004, Theoretical Biology and Medical Modelling.