Zwolak J W, Tyson J J, Watson L T
Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0106, USA.
Syst Biol (Stevenage). 2005 Jun;152(2):81-92. doi: 10.1049/ip-syb:20045032.
DNA synthesis and nuclear division in the developing frog egg are controlled by fluctuations in the activity of M-phase promoting factor (MPF). The biochemical mechanism of MPF regulation is most easily studied in cytoplasmic extracts of frog eggs, for which careful experimental studies of the kinetics of phosphorylation and dephosphorylation of MPF and its regulators have been made. In 1998 Marlovits et al. used these data sets to estimate the kinetic rate constants in a mathematical model of the control system originally proposed by Novak & Tyson. In a recent publication, we showed that a gradient-based optimisation algorithm finds a locally optimal parameter set quite close to the 'Marlovits' estimates. In this paper, we combine global and local optimisation strategies to show that the 'refined Marlovits' parameter set, with one minor but significant modification to the Novak & Tyson equations, is the unique, best-fitting solution to the parameter estimation problem.
发育中的蛙卵中的DNA合成和核分裂受M期促进因子（MPF）活性波动的控制。MPF调节的生化机制在蛙卵的细胞质提取物中最容易研究，针对此已对MPF及其调节因子的磷酸化和去磷酸化动力学进行了细致的实验研究。1998年，马尔洛维茨等人利用这些数据集在诺瓦克和泰森最初提出的控制系统数学模型中估算动力学速率常数。在最近的一篇论文中，我们表明基于梯度的优化算法找到了一个非常接近“马尔洛维茨”估算值的局部最优参数集。在本文中，我们结合全局和局部优化策略，表明对诺瓦克和泰森方程进行一处微小但重要的修改后的“改进的马尔洛维茨”参数集是参数估计问题的唯一最佳拟合解决方案。
