Speakers
Description
Gene expression is inherently stochastic and controlled at multiple stages, including epigenetic and transcriptional regulation. These processes are complex and often result in multimodal distributions. For example, the presence or absence of DNA methylation at a given genomic location exhibits a generally bimodal distribution, which can be linked to transcriptional variability. Likewise, gene regulatory networks give rise to multimodal protein distributions, with random transitions between the modes contributing to cell fate decisions. Advances in single-cell sequencing and the availability of large epigenomic datasets have increased the interest in utilizing mathematical models to understand these processes. However, standard approaches for stochastic chemical kinetics have drawbacks, such as long simulation times for the Stochastic Simulation Algorithm (SSA), especially for multimodal distributions, or impractically large system sizes for the Chemical Master Equation (CME). This minisympsium highlights methods that have been developed to overcome these drawbacks. This includes (1) an efficient mean-field CME approximation, which quantitatively recapitulates methylation bimodality \cite{bonsu2024tunable}, (2) a hybrid discrete/continuous model for transcriptional bursting \cite{fournie2025cell}, (3) a domain decomposition approach for SSA \cite{yousefian2025efficient}, and (4) neural networks for learning the macroscopic dynamics \cite{yousefian2025exploring}.
Bibliography
@article{fournie2025cell,
title={Cell Trajectory Inference based on {S}chr{\"o}dinger Problem and a Mechanistic Model of Stochastic Gene Expression},
author={Fourni{\'e}, Cl{\'e}mence and Ventre, Elias and Herbach, Ulysse and Baradat, Aymeric and Gandrillon, Olivier and Crauste, Fabien},
journal={bioRxiv},
pages={2025--11},
year={2025},
publisher={Cold Spring Harbor Laboratory}
}
@article{yousefian2025efficient,
title={Efficient construction of {M}arkov state models for stochastic gene regulatory networks by domain decomposition},
author={Yousefian, Maryam and Frank, Anna-Simone and Weber, Marcus and R{\"o}blitz, Susanna},
journal={BMC Bioinformatics},
volume={26},
number={1},
pages={147},
year={2025},
publisher={Springer}
}
@inproceedings{yousefian2025exploring,
title={Exploring Metastable Dynamics of Gene Regulatory Networks with {ISOKANN}},
author={Yousefian, Maryam and Donati, Luca and Sikorski, Alexander and Weber, Marcus and R{\"o}blitz, Susanna},
booktitle={International Conference on Computational Methods in Systems Biology},
pages={126--149},
year={2025},
organization={Springer}
}
@article{bonsu2024tunable,
title={A Tunable, Ultrasensitive Threshold in Enzymatic Activity Governs the {DNA} Methylation Landscape},
author={Bonsu, Kwadwo A and Trinh, Annie and Downing, Timothy L and Read, Elizabeth L},
journal={bioRxiv},
pages={2024--06},
year={2024},
publisher={Cold Spring Harbor Laboratory}
}
