9 citations · 34 across the 12 of their papers we have counts for
12 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…
Reliable ligand discrimination in stochastic multistep kinetic proofreading: First passage time vs. product counting strategies
Xiangting Li, Tom Chou
Cellular signaling, crucial for biological processes like immune response and homeostasis, relies on specificity and fidelity in signal transduction to accurately respond to stimul…
Perturbative adaptive importance sampling for Bayesian LOO cross-validation
Joshua C Chang, Xiangting Li, Tianyi Su +4
Importance sampling (IS) is an efficient stand-in for model refitting in performing (LOO) cross-validation (CV) on a Bayesian model. IS inverts the Bayesian update for a single obs…
Squared Wasserstein-2 Distance for Efficient Reconstruction of Stochastic Differential Equations
Mingtao Xia, Xiangting Li, Qijing Shen +1
We provide an analysis of the squared Wasserstein-2 () distance between two probability distributions associated with two stochastic differential equations (SDEs). Based on th…
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations
Mingtao Xia, Xiangting Li, Qijing Shen +1
Rapidly developing machine learning methods has stimulated research interest in computationally reconstructing differential equations (DEs) from observational data which may provid…
Stochastic nucleosome disassembly mediated by remodelers and histone fragmentation
Xiangting Li, Tom Chou
We construct and analyze monomeric and multimeric models of the stochastic disassembly of a single nucleosome. Our monomeric model predicts the time needed for a number of histone-…
The role of APOBEC3-induced mutations in the differential evolution of monkeypox virus
Xiangting Li, Sara Habibipour, Tom Chou +1
Recent studies show that newly sampled monkeypox virus (MPXV) genomes exhibit mutations consistent with Apolipoprotein B mRNA Editing Catalytic Polypeptide-like3 (APOBEC3)-mediated…
Overcompensation of transient and permanent death rate increases in age-structured models with cannibalistic interactions
Mingtao Xia, Xiangting Li, Tom Chou
There has been renewed interest in understanding the mathematical structure of ecological population models that lead to overcompensation, the process by which a population recover…
Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling
Xiangting Li, Tom Chou
Under certain cellular conditions, transcription and mRNA translation in prokaryotes appear to be "coupled," in which the formation of mRNA transcript and production of its associa…