Dynamic reprogramming of transcriptional networks enables cells to adapt to a changing
environment. Thus, it is crucial not only to understand what gene targets are regulated by a …

Versatile tools for gene expression regulation are vital for engineering gene networks of
increasing scales and complexity with bespoke responses. Here, we investigate and …

Identifying the general principles by which genotypes are converted into phenotypes
remains a challenge in the post-genomic era. We still lack a predictive understanding of how …

Inside individual cells, stochastic expression drives random fluctuations in gene product
copy numbers, which corrupts functioning of both natural and synthetic genetic circuits …

Avian pathogenic E. coli (APEC) can cause localized or systemic infection, resulting in large
economic losses per year, and impact health of humans. Previous studies showed that RIP2 …

Piecewise deterministic Markov processes (PDMP) are a class of mathematical models that
integrates discrete stochastic events with continuous deterministic dynamics. The exact …

Gene expression is intrinsically a stochastic (noisy) process with important implications for
cellular functions. Deciphering the underlying mechanisms of gene expression noise …

The genome contains several high-affinity non-functional binding sites for transcription
factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the …

RNA polymerase (RNAP) is the workhorse of bacterial gene expression, transcribing rRNA
and mRNA. Experiments found that a significant fraction of RNAPs in bacteria are …

Expression of many genes varies as a cell transitions through different cell-cycle stages.
How coupling between stochastic expression and cell cycle impacts cell-to-cell variability …