10042 2025 eng 147 26 article 0 2025-06-02 -- -- 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 dynamics of the system is encoded in the spectral properties of the CME operator. Markov State Models (MSMs) provide a general framework for analyzing and visualizing stochastic multistability and state transitions based on these spectral properties. Until now, however, this approach is either limited to low-dimensional systems or requires the use of high-performance computing facilities, thus limiting its usability. BMC Bioinformatics 10.1186/s12859-025-06174-5 yes publish false true Maryam Yousefian Marcus Weber Anne-Simone Frank Marcus Weber Susanna Röblitz Weber, Marcus Modeling and Simulation of Complex Processes MathPlusAA1-15