Horizontal gene transfer mediated by bacteriophages is a critical mechanism for bacterial genome plasticity, among others, responsible for the diffusion of antibiotic resistance. We develop a stochastic Chemical Reaction Network (CRN) model capturing phage-mediated communication between engineered Sender and Receiver E. coli populations, where M13 bacteriophages transport genetic sequences,...
Plasmids are extrachromosomal DNA molecules widely used in synthetic biology to implement gene circuits and control protein production. At the single-cell level, plasmids replicate stochastically and segregate at division, generating copy-number variability, while at the population level cell growth and division shape plasmid distributions. Existing models typically focus on either...
Gene expression models often treat the cell cycle as mere background, overlooking the transient gene-dosage shifts introduced by DNA replication. We ask how these dosage changes reshape the time it takes single cells to cross regulatory thresholds—a key currency for decision-making in transcriptional networks. Using a general stochastic framework that captures cell-to-cell variability without...
Inferring gene regulatory interactions from transcriptomic data is crucial for understanding gene networks. It is made difficult by technical noise, cell size and other confounding factors which introduce spurious correlations and inference errors. Focusing on regulation via coding and non-coding RNA interactions, we generalise correlation tests in the presence of technical noise to allow...
Biochemical processes inside cells are fundamentally stochastic. Inferring parameters of stochastic models describing these processes from collected single-cell data poses mathematical and computational problems. This minisymposium brings together international speakers who will present recent methodological advances on modeling and inference with different types of single-cell data. Juan...
