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We investigate a quantitative network of gene expression dynamics describing the competence development in Bacillus subtilis. First, we introduce an Onsager-Machlup approach to quantify the most probable transition pathway for both excitable and bistable dynamics. Then, we apply a machine learning method to calculate the most probable transition pathway via the Euler-Lagrangian equation. Finally, we analyze how the noise intensity affects the transition phenomena.


Jianyu Hu, Xiaoli Chen, Jinqiao Duan. An Onsager-Machlup approach to the most probable transition pathway for a genetic regulatory network. Chaos (Woodbury, N.Y.). 2022 Apr;32(4):041103

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PMID: 35489871

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