CBE Seminar: Elizabeth Read; University of California, Irvine
Title: "Noisy-omics: Statistical Inference and Biochemical Network Modeling to Shed Light on Gene Regulation."
Cell biological data is increasingly available at single-cell, single-nucleotide, and single-molecule resolution. Such experiments reveal often-unexpected levels of heterogeneity at these scales. In the Read lab, we use stochastic modeling to quantitatively describe this heterogeneity and infer mechanistic insights from data.
I will present recent work in two areas: epigenetics and gene regulatory networks in development. In both areas, we combine “-omic” datasets and statistical analyses with stochastic biochemical reaction network modeling to gain insights from noise signatures in the data. Specifically, we find that genomic regional correlations derived from pulse-chase experiments on post-replication DNA methylation can be used to discriminate between enzymatic model assumptions. In the second area, we are pursuing the use of stochastic models of gene regulatory networks to develop optimally informative statistical measures that discriminate between gene regulation models on the basis of single cell transcriptomics.
Elizabeth Read is an Assistant Professor in the Department of Chemical & Biomolecular Engineering at the University of California, Irvine. She obtained undergraduate degrees in Chemistry and Mathematics at the University of Colorado, obtained a PhD in physical chemistry at the University of California, Berkeley, and was a Jane Coffin Childs Postdoctoral Fellow in Chemical Engineering at MIT. Read is a member of the UC Irvine Center for Complex Biological Systems and the NSF-Simons Center for Multiscale Cell Fate. She is a current Scialog Fellow and has received the UC Irvine Professor of the Year award in Chemical Engineering.
Zoom Meeting ID: 943 3343 2573
Tuesday, September 29, 2020 at 4:00pm to 5:00pmVirtual Event