A new parametric method to smooth time-series data of metabolites in metabolic networks.
Mathematical modeling of large-scale metabolic networks usually requires smoothing of metabolite time-series data to account for measurement or biological errors. Accordingly, the accuracy of smoothing curves strongly affects the subsequent estimation of model parameters. Here, an efficient parametric method is proposed for smoothing metabolite time-series data, and its performance is evaluated. To simplify parameter estimation, the method uses S-system-type equations with simple power law-type efflux terms. Iterative calculation using this method was found to readily converge, because parameters are estimated stepwise. Importantly, smoothing curves are determined so that metabolite concentrations satisfy mass balances. Furthermore, the slopes of smoothing curves are useful in estimating parameters, because they are probably close to their true behaviors regardless of errors that may be present in the actual data. Finally, calculations for each differential equation were found to converge in much less than one second if initial parameters are set at appropriate (guessed) values.
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.
Atsuko
A
Miyawaki
RIKEN Center for Sustainable and Resource Science, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.
Kansuporn
K
Sriyudthsak
RIKEN Center for Sustainable and Resource Science, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.
Masami Yokota
MY
Hirai
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 . Electronic address: fumishira@brs.kyushu-u.ac.jp.
Fumihide
F
Shiraishi
D053858:Metabolic Networks and Pathways; D055442:Metabolome; D008954:Models, Biological
Biochemical systems theory; Convergent calculation; Data smoothing; Metabolite concentration; Parameter estimation