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Article Dans Une Revue Frontiers in Molecular Biosciences Année : 2021

WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically

Vincent Noël
Marco Ruscone
  • Fonction : Auteur
Gautier Stoll
Eric Viara
  • Fonction : Auteur
Andrei Zinovyev

Résumé

WebMaBoSS is an easy-to-use web interface for conversion, storage, simulation and analysis of Boolean models that allows to get insight from these models without any specific knowledge of modeling or coding. It relies on an existing software, MaBoSS, which simulates Boolean models using a stochastic approach: it applies continuous time Markov processes over the Boolean network. It was initially built to fill the gap between Boolean and continuous formalisms, i.e., providing semi-quantitative results using a simple representation with a minimum number of parameters to fit. The goal of WebMaBoSS is to simplify the use and the analysis of Boolean models coping with two main issues: 1) the simulation of Boolean models of intracellular processes with MaBoSS, or any modeling tool, may appear as non-intuitive for non-experts; 2) the simulation of already-published models available in current model databases (e.g., Cell Collective, BioModels) may require some extra steps to ensure compatibility with modeling tools such as MaBoSS. With WebMaBoSS, new models can be created or imported directly from existing databases. They can then be simulated, modified and stored in personal folders. Model simulations are performed easily, results visualized interactively, and figures can be exported in a preferred format. Extensive model analyses such as mutant screening or parameter sensitivity can also be performed. For all these tasks, results are stored and can be subsequently filtered to look for specific outputs.
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Origine : Publication financée par une institution

Dates et versions

hal-03479335 , version 1 (14-12-2021)

Identifiants

Citer

Vincent Noël, Marco Ruscone, Gautier Stoll, Eric Viara, Andrei Zinovyev, et al.. WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically. Frontiers in Molecular Biosciences, 2021, 8, ⟨10.3389/fmolb.2021.754444⟩. ⟨hal-03479335⟩
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