• TUCS Publication Series
• How to Publish in TUCS Series
• Publication Search
• Publication Graph
• Publication Input
• Publication Input Guide
• JuFo Browser

Complete Characterization for the Fit-Preserving Data Refinement of Mass-Action Reaction Networks

Cristian Gratie, Ion Petre, Complete Characterization for the Fit-Preserving Data Refinement of Mass-Action Reaction Networks. Theoretical Computer Science 641, 11–24, 2016.

http://dx.doi.org/10.1016/j.tcs.2016.03.027

Abstract:

The data refinement of reaction-based models consists in substituting species from the original model with several subspecies in the refined one. Fit-preserving refinement, where the goal is to capture the same species dynamics as the original model, helps reduce the computational cost of model fitting by reusing previously fit rate constants. In this paper we give a complete characterization of fit-preserving refinement, as necessary and sufficient linear constraints on the reaction rate constants. Our result is applicable for mass-action reaction networks with uniquely identifiable rate constants. We demonstrate our result on the well-known Brusselator model.

BibTeX entry:

@ARTICLE{jGrPe16a,
  title = {Complete Characterization for the Fit-Preserving Data Refinement of Mass-Action Reaction Networks},
  author = {Gratie, Cristian and Petre, Ion},
  journal = {Theoretical Computer Science},
  volume = {641},
  publisher = {Elsevier},
  pages = {11–24},
  year = {2016},
  keywords = {Biomodeling; Model fit; Quantitative model refinement; Fit-preserving refinement; Canonical refinement; Brusselator},
  ISSN = {0304-3975},
}

Belongs to TUCS Research Unit(s): Computational Biomodeling Laboratory (Combio Lab)

Publication Forum rating of this publication: level 2

Edit publication