Automated inference of Boolean models from molecular interaction maps using CaSQ - Inria - Institut national de recherche en sciences et technologies du numérique
Journal Articles Bioinformatics Year : 2020

Automated inference of Boolean models from molecular interaction maps using CaSQ

Abstract

Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behavior of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner. We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of SBGN standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, SBML-qual, that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability. The present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq
Fichier principal
Vignette du fichier
btaa484(1).pdf (657.06 Ko) Télécharger le fichier
Origin Publication funded by an institution

Dates and versions

hal-02590714 , version 1 (11-01-2021)

Identifiers

Cite

Sara Sadat Aghamiri, Vidisha Singh, Aurélien Naldi, Tomáš Helikar, Sylvain Soliman, et al.. Automated inference of Boolean models from molecular interaction maps using CaSQ. Bioinformatics, 2020, 36 (16), pp.4473-4482. ⟨10.1093/bioinformatics/btaa484⟩. ⟨hal-02590714⟩
226 View
176 Download

Altmetric

Share

More