### Abstract

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.

Original language | English |
---|---|

Title of host publication | Computer Algebra in Scientific Computing - 10th International Workshop, CASC 2007, Proceedings |

Pages | 433-447 |

Number of pages | 15 |

Publication status | Published - Dec 1 2007 |

Event | 10th International Workshop Computer Algebra in Scientific Computing, CASC 2007 - Bonn, Germany Duration: Sep 16 2007 → Sep 20 2007 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|

Volume | 4770 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 10th International Workshop Computer Algebra in Scientific Computing, CASC 2007 |
---|---|

Country | Germany |

City | Bonn |

Period | 9/16/07 → 9/20/07 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Computer Algebra in Scientific Computing - 10th International Workshop, CASC 2007, Proceedings*(pp. 433-447). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4770 LNCS).

**An algebraic-numeric algorithm for the model selection in kinetic networks.** / Yoshida, Hiroshi; Nakagawa, Koji; Anai, Hirokazu; Horimoto, Katsuhisa.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Computer Algebra in Scientific Computing - 10th International Workshop, CASC 2007, Proceedings.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4770 LNCS, pp. 433-447, 10th International Workshop Computer Algebra in Scientific Computing, CASC 2007, Bonn, Germany, 9/16/07.

}

TY - GEN

T1 - An algebraic-numeric algorithm for the model selection in kinetic networks

AU - Yoshida, Hiroshi

AU - Nakagawa, Koji

AU - Anai, Hirokazu

AU - Horimoto, Katsuhisa

PY - 2007/12/1

Y1 - 2007/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=38149010446&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38149010446&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9783540751861

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 433

EP - 447

BT - Computer Algebra in Scientific Computing - 10th International Workshop, CASC 2007, Proceedings

ER -