Recent experimental developments in genome-wide RNA quantification hold considerable
promise for systems biology. However, rigorously probing the biology of living cells requires …

The question of how cell-to-cell differences in transcription rate affect RNA count
distributions is fundamental for understanding biological processes underlying transcription …

The advent of high-throughput transcriptomics provides an opportunity to advance
mechanistic understanding of transcriptional processes and their connections to cellular …

Heterogeneity is a dominant factor in the behaviour of many biological processes. Despite
this, it is common for mathematical and statistical analyses to ignore biological heterogeneity …

The chemical master equation (CME) is a fundamental description of interacting molecules
commonly used to model chemical kinetics and noisy gene regulatory networks. Exact time …

The finite state projection (FSP) approach to solving the chemical master equation has
enabled successful inference of discrete stochastic models to predict single-cell gene …

Stochastic reaction network models are often used to explain and predict the dynamics of
gene regulation in single cells. These models usually involve several parameters, such as …

The chemical master equation (CME), which describes the discrete and stochastic molecule
number dynamics associated with biological processes like transcription, is difficult to solve …

Resolving practical non-identifiability of computational models typically requires either
additional data or non-algorithmic model reduction, which frequently results in models …

Fisher information is a lower bound on the uncertainty in the statistical estimation of classical
and quantum mechanical parameters. While some deterministic dynamical systems are not …