A new parametric method to smooth time-series data of metabolites in metabolic networks

Atsuko Miyawaki, Kansuporn Sriyudthsak, Masami Yokota Hirai, Fumihide Shiraishi

研究成果: ジャーナルへの寄稿記事

2 引用 (Scopus)

抄録

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.

元の言語英語
ページ(範囲)21-33
ページ数13
ジャーナルMathematical Biosciences
282
DOI
出版物ステータス出版済み - 12 1 2016

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Metabolic Network
Metabolites
Time Series Data
Metabolic Networks and Pathways
Smoothing
Time series
time series analysis
metabolites
Curve
Parameter estimation
Differential equations
Converge
mathematical models
S-system
methodology
Mathematical Modeling
Parameter Estimation
Slope
Simplify
Power Law

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

これを引用

A new parametric method to smooth time-series data of metabolites in metabolic networks. / Miyawaki, Atsuko; Sriyudthsak, Kansuporn; Hirai, Masami Yokota; Shiraishi, Fumihide.

:: Mathematical Biosciences, 巻 282, 01.12.2016, p. 21-33.

研究成果: ジャーナルへの寄稿記事

Miyawaki, Atsuko ; Sriyudthsak, Kansuporn ; Hirai, Masami Yokota ; Shiraishi, Fumihide. / A new parametric method to smooth time-series data of metabolites in metabolic networks. :: Mathematical Biosciences. 2016 ; 巻 282. pp. 21-33.
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