复杂生物过程的仿真分析

Simulation and Analysis of Complex Biological Processes

随着系统生物学研究的不断深入,生物过程网络的规模逐步拓展,模型的复杂程度也越来越高,客观上需要不同的分析方法去应对。针对典型的酿酒酵母糖酵解途径和流行病免疫防治过程的动态模型,分别利用Matlab和开源计算工具CVODE进行常规的数值积分求解,其结果与文献报道吻合;以此作为参照,将生物过程的动态模型离散化后利用基于内点法的非线性规划解题器IPOPT进行数学规划求解,计算结果显示,Matlab、CVODE及IPOPT对不同类型、规模的动态模型有不同的适用性;通过调整模型的离散参数,IPOPT可得到与参照一致的仿真结果,这表明非线性规划可作为分析优化生物过程这类大规模复杂系统的方法。

With the development of research on Systems Biology and the biological process network scale gradually expanded, the model increasingly became more complex. Objectively, it required multiple analysis methods to deal with. Aimed at the dynamic model of glycolysis pathway of Saccharomyces cerevisiae and the epidemic control process, the model was solved by Matlab and CVODE using conventional numerical integration solution, and the results agreed with the reported data. After discretization the dynamic models were solved by IPOPT which was a famous nonlinear programming solver. The results were shown to be consistent with the control subject. By compercomparison, these three solvers had different applicability on different types of problems, and nonlinear programming could be used as a novel approach for the optimization of biological process.