Chen Jia

Spectral theory of stochastic gene expression: a Hilbert space framework

This paper provides a unified Hilbert space framework for the spectral theory of stochastic gene expression and shows that deterministic models fail to capture relaxation rates under strong autoregulation.

Exact switching time distributions for autoregulated gene expression models with mRNA and protein descriptions

This study derives exact switching time distributions for a stochastic model of autoregulatory gene expression, showing that explicit mRNA dynamics lead to new distribution shapes not captured by reduced models.

Effective Markovian dynamics method of solving non-Markovian dynamics of stochastic gene expression

This paper develops an effective Markovian dynamics method to solve non-Markovian gene expression models and shows it explains reduced mRNA-protein correlation and enhanced bimodality in non-exponential protein decay.

Holimap: an accurate and efficient method for solving stochastic gene network dynamics

Holimap approximates gene network dynamics using a simpler reaction system, showing computational advantages over conventional methods in predicting stochastic time-dependent dynamics.

Solving the time-dependent protein distributions for autoregulated bursty gene expression using spectral decomposition

This study provides an exact time-dependent solution for the CME of a gene circuit with autoregulation and bursty expression using spectral decomposition.

Poisson representation: a bridge between discrete and continuous models of stochastic gene regulatory networks

This paper investigates the Poisson representation linking discrete and continuous models of stochastic gene regulatory networks, showing it holds for unregulated genes and approximates for regulated ones in large protein number limits.

Analytical time-dependent distributions for gene expression models with complex promoter switching mechanisms

The paper derives time-dependent distributions for gene expression models with complex promoter switching, showing molecular memory affects bimodality depending on switching rates.

Coupling gene expression dynamics to cell size dynamics and cell cycle events: exact and approximate solutions of the extended telegraph model

The paper derives analytical solutions for an extended telegraph model that incorporates cell cycle and growth effects on mRNA fluctuations, showing a linear relationship between mRNA and cell volume fluctuations.

Concentration fluctuations due to size-dependent gene expression and cell-size control mechanisms

The paper models gene expression and cell size dynamics to analyze concentration fluctuations and homeostasis in E. coli, fission yeast, and budding yeast.

Characterizing non-exponential growth and bimodal cell size distributions in Schizosaccharomyces pombe: an analytical approach

This paper develops a stochastic model to explain non-exponential growth and bimodal cell size distributions in fission yeast, showing how growth phases and control strategies shape these distributions.

Frequency domain analysis of fluctuations of mRNA and protein copy numbers within a cell lineage: theory and experimental validation

The paper develops a theoretical framework to analyze mRNA and protein fluctuations in cell lineages and validates it using E. coli data, showing how power spectrum features reveal gene expression mechanisms.

Cell size distribution of lineage data: analytic results and parameter inference

The paper develops a mathematical model to analyze cell size distribution in lineage data and validates it against experimental E. coli data.

Dynamical phase diagram of an auto-regulating gene in fast switching conditions

The paper analyzes the time-dependent behavior of an auto-regulating gene under fast promoter switching, identifying six dynamical phases based on parameter space and stochastic dynamics.

Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data

The paper provides a kinetic foundation for the zero-inflated negative binomial model in single-cell RNA sequencing by linking it to transcriptional bursting and dropout events.