An Algebraic-Numeric Algorithm for the Model Selection in Kinetic Networks

  • Hiroshi Yoshida
  • Koji Nakagawa
  • Hirokazu Anai
  • Katsuhisa Horimoto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4770)


We propose a novel algorithm to select a model that is consistent with the time series of observed data. In the first step, the kinetics for describing a biological phenomenon is expressed by a system of differential equations, assuming that the relationships between the variables are linear. Simultaneously, the time series of the data are numerically fitted as a series of exponentials. In the next step, both the system of differential equations with the kinetic parameters and the series of exponentials fitted to the observed data are transformed into the corresponding system of algebraic equations, by the Laplace transformation. Finally, the two systems of algebraic equations are compared by an algebraic approach. The present method estimates the model’s consistency with the observed data and the determined kinetic parameters. One of the merits of the present method is that it allows a kinetic model with cyclic relationships between variables that cannot be handled by the usual approaches. The plausibility of the present method is illustrated by the actual relationships between specific leaf area, leaf nitrogen and leaf gas exchange with the corresponding simulated data.


Model Selection Directed Acyclic Graph Leaf Nitrogen Model Consistency Consistency Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hiroshi Yoshida
    • 1
  • Koji Nakagawa
    • 2
  • Hirokazu Anai
    • 3
  • Katsuhisa Horimoto
    • 2
  1. 1.Faculty of Mathematics, Organization for the Promotion of Advanced Research, Kyushu University, Hakozaki 6-10-1, Higashi-ku, Fukuoka 812-8581Japan
  2. 2.Computational Biology Research Centre (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi 2-42, Koto-ku, Tokyo 135-0064Japan
  3. 3.IT Core Laboratories, FUJITSU LABORATORIES LTD./CREST, JST., Kamikodanaka 4-1-1, Nakahara-ku, Kawasaki 211-8588Japan

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