A Large-Scale Assessment of Exact Model Reduction in the BioModels Repository

Isabel Cristina Pérez-Verona*, Mirco Tribastone, Andrea Vandin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Chemical reaction networks are a popular formalism for modeling biological processes which supports both a deterministic and a stochastic interpretation based on ordinary differential equations and continuous-time Markov chains, respectively. In most cases, these models do not enjoy analytical solution, thus typically requiring expensive computational methods based on numerical solvers or stochastic simulations. Exact model reduction techniques can be used as an aid to lower the analysis cost by providing reduced networks that preserve the dynamics of interest to the modeler. We hereby consider a family of techniques for both deterministic and stochastic networks which are based on equivalence relations over the species in the network, leading to a coarse graining which provides the exact aggregate time-course evolution for each equivalence class. We present a large-scale empirical assessment on the BioModels repository by measuring their compression capability over 667 models. Through a number of selected case studies, we also show their ability in yielding physically interpretable reductions that can reveal dynamical patterns of the bio-molecular processes under consideration.

Original languageEnglish
Title of host publicationProceedings of 17th International Conference on Computational Methods in Systems Biology
EditorsLuca Bortolussi, Guido Sanguinetti
Number of pages18
PublisherSpringer
Publication date1 Jan 2019
Pages248-265
ISBN (Print)9783030313036
DOIs
Publication statusPublished - 1 Jan 2019
Event17th International Conference on Computational Methods in Systems Biology, CMSB 2019 - Trieste, Italy
Duration: 18 Sep 201920 Sep 2019

Conference

Conference17th International Conference on Computational Methods in Systems Biology, CMSB 2019
CountryItaly
CityTrieste
Period18/09/201920/09/2019
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11773 LNBI
ISSN0302-9743

Keywords

  • Biological systems
  • Equivalence relations
  • Model reduction

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