An Algebraic-Numeric Algorithm for the Model Selection in Network Motifs in Escherichia coli
Recently, we have proposed a novel algorithm to select a model that is the most consistent with the time series of observed data. In the algorithm, first, a system of differential equations that express the kinetics for a biological phenomenon and a sum of exponentials that are fitted to the observed data are transformed into the corresponding system of algebraic equations, by the Laplace transformation. Then, the two systems of algebraic equations are compared by an algebraic-numeric approach. One of the merits of our algorithm estimates the models consistency with the observed data and the determined kinetic constants. Furthermore, our algorithm allows a kinetic model with cyclic relationships between variables that cannot be handled by the usual approaches. In this paper,we examined the performance of our proposed algorithm by using three kinds of highly significant network motifs in Escherichia coil; feed-forward loop, single input module, dense overlapping reguions, which are found by Shen-Orr, et al14.
Masahiko Nakatsui Hiroshi Yoshida Katsuhisa Horimoto
Computational Biology Research Center CBRC, National Institute of Advanced Industrial Science and Te Faculty of Mathematics, Organization for the Promotion of Advanced Research, Kyushu University, Hako
国际会议
The Second International Symposium(OSB08)(第二届国际优化及系统生物学学术会议)
云南丽江
英文
257-264
2008-10-31（万方平台首次上网日期，不代表论文的发表时间）