Laufer Center Seminar - Ramon Grima

Ramon Grima, Ph.D.

Professor (Chair of Mathematical Biology), School of Biological Sciences, University of Edinburgh Edinburgh, UK

March 16, 2026 at 1:00 PM

Laufer Center Lecture Hall 101

Title: Stochastic Gene Expression: Modeling and Inference from Single-Cell Data

Abstract: Gene expression is intrinsically stochastic, leading to substantial cell-to-cell variability in mRNA and protein levels, now routinely quantified with single-cell technologies. In this talk, I will show how mathematical modeling can reveal the origins, regulation, and functional impact of cellular noise, and how fitting models to single-cell data allows mechanistic inference of gene expression dynamics. I will first introduce a set of theoretical frameworks developed in my group for analyzing stochastic biochemical networks beyond classical deterministic or linear-noise descriptions. Next, I will discuss extensions of the classical two-state telegraph model to incorporate salient features of single-cell biology, including cell division, DNA replication, mRNA maturation, gene dosage compensation, growth-dependent transcription, cell-size control strategies and cell-cycle duration variability. Finally, I will present our statistical inference and machine learning approaches for fitting both classical and complex gene-expression models to single-cell data (smFISH, live-cell imaging, and scRNA-seq). These frameworks provide principled ways to separate biological from technical noise, estimate transcriptional parameters, and infer the mechanisms most compatible with observed transcriptional dynamics.

Host: Ivet Bahar & Ken Dill