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Computational Heuristics for Simplifying a Biological Model

Ion Petre, Andrzej Mizera, Ralph-Johan Back, Computational Heuristics for Simplifying a Biological Model. In: Klaus Löwe Benedikt Merkle Wolfgang Ambos-Spies (Ed.), Mathematical Theory and Computational Practice: 5th Conference on Computability in Europe, CiE 2009, Proceedings, Lecture Notes in Computer Science 5635, 399–408, Springer, 2009.

Abstract:

Computational modeling efforts for biological processes adopt either of the following strategies: strive to build large, as complete as possible models in an effort to obtain very realistic models, or on the contrary, build as simple as possible models focusing only on the core aspects of the process, in an effort to obtain a model that is easier to analyze, fit, and validate. When the latter strategy is adopted, the aspects that are left outside the models are very often up to the subjective options of the modeler. We show in this paper a heuristic method to
simplify an already fit model in such a way that the numerical fit to the experimental data is not lost. We focus in particular on eliminating some of the variables of the model and the reactions they take part in, while also modifying some of the remaining reactions. We illustrate the method on a computational model for the eukaryotic heat shock response.

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BibTeX entry:

@INPROCEEDINGS{inpPeMiBa09a,
  title = {Computational Heuristics for Simplifying a Biological Model},
  booktitle = {Mathematical Theory and Computational Practice: 5th Conference on Computability in Europe, CiE 2009, Proceedings},
  author = {Petre, Ion and Mizera, Andrzej and Back, Ralph-Johan},
  volume = {5635},
  series = {Lecture Notes in Computer Science},
  editor = {Ambos-Spies, Klaus Löwe Benedikt Merkle Wolfgang},
  publisher = {Springer},
  pages = {399–408},
  year = {2009},
  keywords = {Model reduction, heat shock response, mathematical model},
}

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

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