4 papers
A generalized work theorem for stopped stochastic chemical reaction networks
Xiangting Li, Tom Chou
We establish a generalized work theorem for stochastic chemical reaction networks (CRNs). By using a compensated Poisson jump process, we identify a martingale structure in a gener…
Reconstructing Noisy Gene Regulation Dynamics Using Extrinsic-Noise-Driven Neural Stochastic Differential Equations
Jiancheng Zhang, Xiangting Li, Xiaolu Guo +6
Proper regulation of cell signaling and gene expression is crucial for maintaining cellular function, development, and adaptation to environmental changes. Reaction dynamics in cel…
Martingale properties of entropy production and a generalized work theorem with decoupled forward and backward processes
Xiangting Li, Tom Chou
By decoupling forward and backward stochastic trajectories, we construct a family of martingales and work theorems for both overdamped and underdamped Langevin dynamics. Our result…
An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks
Mingtao Xia, Xiangting Li, Qijing Shen +1
We analyze the Wasserstein distance (-distance) between two probability distributions associated with two multidimensional jump-diffusion processes. Specifically, we analyze a t…