MaBoSS 2.0: An environment for stochastic Boolean modeling

Gautier Stoll, Barthélémy Caron, Eric Viara, Aurélien Dugourd, Andrei Zinovyev, Aurélien Naldi, Guido Kroemer, Emmanuel Barillot, Laurence Calzone

    Research output: Contribution to journalArticlepeer-review

    80 Citations (Scopus)

    Abstract

    Motivation: Modeling of signaling pathways is an important step towards the understanding and the treatment of diseases such as cancers, HIV or auto-immune diseases. MaBoSS is a software that allows to simulate populations of cells and to model stochastically the intracellular mechanisms that are deregulated in diseases. MaBoSS provides an output of a Boolean model in the form of time-dependent probabilities, for all biological entities (genes, proteins, phenotypes, etc.) of the model. Results: We present a new version of MaBoSS (2.0), including an updated version of the core software and an environment. With this environment, the needs for modeling signaling pathways are facilitated, including model construction, visualization, simulations of mutations, drug treatments and sensitivity analyses. It offers a framework for automated production of theoretical predictions.

    Original languageEnglish
    Pages (from-to)2226-2228
    Number of pages3
    JournalBioinformatics
    Volume33
    Issue number14
    DOIs
    Publication statusPublished - 15 Jul 2017

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