Simons Foundation Presidential Lectures are free public colloquia centered on four main themes: Biology, Physics, Mathematics and Computer Science, and Neuroscience and Autism Science. These curated, high-level scientific talks feature leading scientists and mathematicians and are intended to foster discourse and drive discovery among the broader NYC-area research community. We invite researchers in the area — as well as interested members of the metropolitan public — to join us for this weekly lecture series.
Transcriptional networks operate dynamically in vivo, but capturing and modeling these dynamics is an experimental and computational challenge. This presentation focuses on time — building predictive network models based on time-series transcriptome data, and perturbing transcription networks in time. The outcome is a dynamic hit-and-run transcription model with relevance across eukaryotes.
In this lecture, Dr. Gloria Coruzzi will probe dynamic transcription networks, computationally and experimentally. Using a machine-learning approach called Dynamic Factor Graph, fine-scale time-series transcriptome data is used to infer network models that were validated both in silico using left-out data, and experimentally. To explore the molecular basis for underlying dynamic transcription, a cell-based assay was developed to follow the mode of action of a transcription factor (TF) within one minute of nuclear entry. This uncovered genome-wide support for a hit-and-run mechanism of transcription, in which de novo transcription initiated by a transient TF “hit” persists after the TF has “run.”