Denis Thieffry | Searcharxiv

arXiv2026

GINsim 3.1: Qualitative modelling and dynamical analysis of logical regulatory networks

GINsim is a software for the definition and dynamical analysis of qualitative (Boolean and multi-valued) models of biological regulatory networks. Building on its modular architecture, based on the MDDlib decision-diagram and bioLQM model-manipulation libraries, GINsim version 3.1 introduces new functionalities aimed at the analysis of large logical models: the symbolic computation of trap-spaces, the Booleanisation of multilevel models and the reversal of model dynamics. GINsim 3.1 also extends the estimation of attractor reachability (Monte Carlo and Avatar algorithms), the computation of stable states, as well as model reduction functionalities. Analyses can be applied to perturbed models, and scripted, in particular from the CoLoMoTo interactive notebook. We illustrate the main functionalities of GINsim on a reference multilevel model of regulatory network that control the mammalian cell cycle, including the computation of its stable states and cyclic attractor, the assessment of their reachability, and the identification of the regulatory circuits driving multistability and oscillations. GINsim is freely available under GPL-3.0 at https://ginsim.github.io/, runs on any platform supporting Java, and is interoperable with the other tools of the CoLoMoTo community. Its website provides installation instructions and reference documentation, as well as a repository of Boolean and multilevel logical models.

q-bio.MN↗

arXiv2013

SBML Qualitative Models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools

Background: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. Results: We present the System Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the cooperative development of the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyze qualitative models. Conclusion: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

q-bio.MN↗