Evolution - Based Gene Regulatory Network of Yeast Cell Cycle

In the work, we try to construct the corresponding S-system and modified power-low model from a dataset. These two mathematical models are highly nonlinear. Though they can clearly describe reactions among genes in the biological system, the identification is a tough work, especially for huge genes. We adopt the evolution strategy to achieve 16-genes modeling with 544 or 288 parameters. The time-course data of the yeast cell cycle is concerned. The proposed two different gene regulatory networks and their corresponding pathways can provide biological researchers for further experiments in yeast cell cycle control.

[1]  R. Singer,et al.  Messenger RNA in HeLa cells: kinetics of formation and decay. , 1973, Journal of molecular biology.

[2]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

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

[4]  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).

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

[6]  Nir Friedman,et al.  Inferring subnetworks from perturbed expression profiles , 2001, ISMB.

[7]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

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

[9]  Satoru Miyano,et al.  Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model , 1998, Pacific Symposium on Biocomputing.

[10]  Hidde de Jong,et al.  Modeling and Simulation of Genetic Regulatory Systems: A Literature Review , 2002, J. Comput. Biol..

[11]  Bor-Sen Chen,et al.  Quantitative characterization of the transcriptional regulatory network in the yeast cell cycle , 2004, Bioinform..