Efficient construction of Markov state models for stochastic gene regulatory networks by domain decomposition

Abstract Background The dynamics of many gene regulatory networks (GRNs) is characterized by the occurrence of metastable phenotypes and stochastic phenotype switches. The chemical master equation (CME) is the most accurate description to model such stochastic dynamics, whereby the long-time dynamic...

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Autors principals:	Maryam Yousefian, Anna-Simone Frank, Marcus Weber, Susanna Röblitz
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2025-06-01
Col·lecció:	BMC Bioinformatics
Matèries:	Gene regulatory networks Stochastic phenotype switching Chemical master equation Markov state modelling Robust Perron cluster analysis Voronoi tessellation
Accés en línia:	https://doi.org/10.1186/s12859-025-06174-5
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