R. M. Ardito Marretta^*, F. Ales^†

Molecular & Cellular Biomechanics, Vol.7, No.4, pp. 225-266, 2010, DOI:10.3970/mcb.2010.007.225

Abstract In this paper, cell cycle in higher eukaryotes and their molecular networks signals both inG1/SandG2/Mtransitions are replicatedin silico. Biochemical kinetics, converted into a set of differential equations, and system control theory are employed to design multi-nested digital layers to simulate protein-to-protein activation and inhibition for cell cycle dynamics in the presence of damaged genomes. Sequencing and controlling the digital process of four micro-scale species networks (p53/Mdm2/DNA damage, p21mRNA/cyclin-CDK complex, CDK/CDC25/wee1/ SKP2/APC/CKI and apoptosis target genes system) not only allows the comprehension of the mechanisms of these molecule interactions but paves the way for unraveling the participants and their by-products, until… More >

Liqiang Lin¹, Xianqiao Wang², Xiaowei Zeng^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.2, pp. 203-220, 2014, DOI:10.3970/cmes.2014.098.203

Abstract The Voronoi tessellation is employed to describe cellular patterns and to simulate cell division and cell remodeling in epithelial tissue. First, Halton sequence is utilized to generate the random generators of Voronoi cell points. The centroidal Voronoi cell center is obtained by probabilistic Lloyd's method and polygonal structure of cell distribution is modeled. Based on the polygonal shape of cells, the instantaneous mechanism of cell division is applied to simulate the cell proliferation and remodeling. Four kinds of single-cell division algorithms are designed with the consideration of cleavage angle. From these simulations, we find that cell topological structure varies case… More >

Tae-Hyuk Ahn¹, Layne T. Watson^1,2, Yang Cao^1,1, Clifford A. Shaffer¹, William T. Baumann³

CMES-Computer Modeling in Engineering & Sciences, Vol.51, No.1, pp. 27-52, 2009, DOI:10.3970/cmes.2009.051.027

Abstract For biochemical systems, where some chemical species are represented by small numbers of molecules, discrete and stochastic approaches are more appropriate than continuous and deterministic approaches. The continuous deterministic approach using ordinary differential equations is adequate for understanding the average behavior of cells, while the discrete stochastic approach accurately captures noisy events in the growth-division cycle. Since the emergence of the stochastic simulation algorithm (SSA) by Gillespie, alternative algorithms have been developed whose goal is to improve the computational efficiency of the SSA. This paper explains and empirically compares the performance of some of these SSA alternatives on a realistic… More >