title: PENDISC: a simple method for constructing a mathematical model from time-series data of metabolite concentrations.
abstract: The availability of large-scale datasets has led to more effort being made to understand characteristics of metabolic reaction networks. However, because the large-scale data are semi-quantitative, and may contain biological variations and/or analytical errors, it remains a challenge to construct a mathematical model with precise parameters using only these data. The present work proposes a simple method, referred to as PENDISC (Parameter Estimation in a N on- DImensionalized S-system with Constraints), to assist the complex process of parameter estimation in the construction of a mathematical model for a given metabolic reaction system. The PENDISC method was evaluated using two simple mathematical models: a linear metabolic pathway model with inhibition and a branched metabolic pathway model with inhibition and activation. The results indicate that a smaller number of data points and rate constant parameters enhances the agreement between calculated values and time-series data of metabolite concentrations, and leads to faster convergence when the same initial estimates are used for the fitting. This method is also shown to be applicable to noisy time-series data and to unmeasurable metabolite concentrations in a network, and to have a potential to handle metabolome data of a relatively large-scale metabolic reaction system. Furthermore, it was applied to aspartate-derived amino acid biosynthesis in Arabidopsis thaliana plant. The result provides confirmation that the mathematical model constructed satisfactorily agrees with the time-series datasets of seven metabolite concentrations.
authors.affiliation: RIKEN Plant Science Center, Yokohama, Kanagawa , 230-0045, Japan.
authors.forename: Kansuporn
authors.initials: K
authors.lastname: Sriyudthsak
authors.forename: Michio
authors.initials: M
authors.lastname: Iwata
authors.forename: Masami Yokota
authors.initials: MY
authors.lastname: Hirai
authors.forename: Fumihide
authors.initials: F
authors.lastname: Shiraishi
mesh_terms: D000596:Amino Acids / Q000096:biosynthesis; D017360:Arabidopsis / Q000378:metabolism; D003198:Computer Simulation; D007700:Kinetics; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological
chemical_list: D000596:Amino Acids