Presentation by Prof. Caroline Uhler, Spring 2021, Math and Statistics Joint Colloquium.
Causal Inference in the Light of Drug Repurposing for COVID-19
https://www.math.ucdavis.edu/research/seminars/?talk_id=6163
Abstract:
Massive data collection holds the promise of a better understanding of
complex phenomena and ultimately, of better decisions. An exciting
opportunity in this regard stems from the growing availability of
perturbation / intervention data (drugs, knockouts, overexpression,
etc.) in biology. In order to obtain mechanistic insights from such
data, a major challenge is the development of a framework that
integrates observational and interventional data and allows predicting
the effect of yet unseen interventions or transporting the effect of
interventions observed in one context to another. I will present a
framework for causal structure discovery based on such data and
highlight the role of overparameterized autoencoders. We end by
demonstrating how these ideas can be applied for drug repurposing in the current SARS-CoV-2 crisis.
