Iwata Michio, Sriyudthsak Kansuporn, Hirai Masami Yokota, Shiraishi Fumihide
Section of Bio-process Design, Department of Bioscience and Biotechnology, Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, 6-10-1, Hakozaki, Higashi-Ku, Fukuoka 820-8581, Japan.
RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan; JST, CREST, Kawaguchi, Saitama 332-0012, Japan.
Math Biosci. 2014 Feb;248:11-21. doi: 10.1016/j.mbs.2013.11.002. Epub 2013 Nov 27.
Metabolic reaction systems can be modeled easily in terms of S-system type equations if their metabolic maps are available. This study therefore proposes a method for estimating parameters in decoupled S-system equations on the basis of the Newton-Raphson method and elucidates the performance of this estimation method. Parameter estimation from the time-course data of metabolite concentrations reveals that the parameters estimated are highly accurate, indicating that the estimation algorithm has been constructed correctly. The number of iterations is small and the calculation converges in a very short time (usually less than 1s). The method is also applied to time course data with noise and found to estimate parameters efficiently. Results indicate that the present method has the potential to be extended to a method for estimating parameters in large-scale metabolic reaction systems.
如果有代谢图谱,代谢反应系统就可以很容易地用S-系统类型方程进行建模。因此,本研究提出了一种基于牛顿-拉夫逊方法的解耦S-系统方程参数估计方法,并阐明了该估计方法的性能。从代谢物浓度的时间进程数据进行参数估计表明,所估计的参数具有很高的准确性,这表明估计算法构建正确。迭代次数少,计算在很短的时间内(通常小于1秒)就收敛。该方法还应用于有噪声的时间进程数据,发现能有效地估计参数。结果表明,本方法有潜力扩展为一种用于估计大规模代谢反应系统参数的方法。