ODEbase: A Repository of ODE Systems for Systems Biology

Christoph Lüders (1) , Thomas Sturm (2, 3, 4) , Ovidiu Radulescu (5, 6)

1 University of Kassel
2 MOSEL - Proof-oriented development of computer-based systems
3 VERIDIS - Modeling and Verification of Distributed Algorithms and Systems
4 MPII - Max-Planck-Institut für Informatik
5 CNRS - Centre National de la Recherche Scientifique
6 UM - Université de Montpellier

Recently, symbolic computation and computer algebra systems have been successfully applied in systems biology, especially in chemical reaction network theory. One advantage of symbolic computation is its potential for qualitative answers to biological questions. Qualitative methods analyze dynamical input systems as formal objects, in contrast to investigating only part of the state space, as is the case with numerical simulation. However, symbolic computation tools and libraries have a different set of requirements for their input data than their numerical counterparts. A common format used in mathematical modeling of biological processes is SBML. We illustrate that the use of SBML data in symbolic computation requires significant pre-processing, incorporating external biological and mathematical expertise. ODEbase provides high quality symbolic computation input data derived from established existing biomodels, covering in particular the BioModels database.

Domaines: Réseaux moléculaires [q-bio.MN]; Calcul formel [cs.SC]; Systèmes dynamiques [math.DS]

Christoph Lüders, Thomas Sturm, Ovidiu Radulescu. ODEbase: A Repository of ODE Systems for Systems Biology. Bioinformatics Advances, 2022, 2 (1), ⟨10.1093/bioadv/vbac027⟩. ⟨hal-03651751⟩