Gautier Stoll1,2,3,4, Barthélémy Caron5, Eric Viara6, Aurélien Dugourd5, Andrei Zinovyev5, Aurélien Naldi7, Guido Kroemer1,2,3,4,8,9,10, Emmanuel Barillot5, Laurence Calzone5. 1. Université Paris Descartes/Paris V, Sorbonne Paris Cité, Paris, France. 2. Gustave Roussy Cancer Campus, Villejuif, France. 3. INSERM, U1138, Paris, France. 4. Equipe 11 labellisée par la Ligue Nationale contre le Cancer, Centre de Recherche des Cordeliers, Paris, France. 5. Institut Curie, PSL Research University, INSERM, U900, Mines Paris Tech, Paris, France. 6. Sysra, Yerres, France. 7. DIMNP UMR CNRS 5235, University of Montpellier, Montpellier, France. 8. Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer Campus, Villejuif, France. 9. Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France. 10. Department of Women's and Children's Health, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden.
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. AVAILABILITY AND IMPLEMENTATION: MaBoSS software can be found at https://maboss.curie.fr , including tutorials on existing models and examples of models. CONTACT: gautier.stoll@upmc.fr or laurence.calzone@curie.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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. AVAILABILITY AND IMPLEMENTATION: MaBoSS software can be found at https://maboss.curie.fr , including tutorials on existing models and examples of models. CONTACT: gautier.stoll@upmc.fr or laurence.calzone@curie.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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