title: Splitting strategy for simulating genetic regulatory networks.
abstract: The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions.
authors.affiliation: Department of Applied Mathematics, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Xiong
authors.initials: X
authors.lastname: You
authors.affiliation: Department of Applied Mathematics, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Xueping
authors.initials: X
authors.lastname: Liu
authors.affiliation: Department of Applied Mathematics, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Ibrahim Hussein
authors.initials: IH
authors.lastname: Musa
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008957:Models, Genetic; D051736:Proto-Oncogene Proteins c-mdm2 / Q000235:genetics*; D012984:Software; D013997:Time Factors; D016159:Tumor Suppressor Protein p53 / Q000235:genetics*
chemical_list: C495901:TP53 protein, human; D016159:Tumor Suppressor Protein p53; C497206:MDM2 protein, human; D051736:Proto-Oncogene Proteins c-mdm2