Nov. 14, 2022: Martin Jankowiak, PhD, Broad Institute

BWH Department of Computational Pathology presents:

2022-23 Junior Investigators Advanced Biomedical Computation (ABC) Seminar Series

“Inferring selection effects in SARS-CoV-2 with Bayesian Viral Allele Selection”

Martin Jankowiak, Ph.D.

Machine Learning Fellow

Broad Institute of Harvard and MIT, Cambridge, MA, USA

Date: Monday, November 14, 2022

Time: 4:00-5:00PM EST

Zoom Link:

Meeting ID: 861 6238 6947

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The SARS-CoV-2 pandemic has been shaped by the repeated emergence of new viral lineages and mutations. Methods to identify emerging variants of epidemiological significance and characterize mutational determinants of enhanced fitness are important for public health. We develop Bayesian Viral Allele Selection (BVAS), a method that leverages the millions of SARS-CoV-2 viral genomes that have been sequenced across the globe to identify mutations linked to increased viral fitness. Ranked lists of top BVAS hits can be used to prioritize lineages and mutations for follow-up study in the lab. By providing a genome-wide view of the evolution of SARS-CoV-2, our principled probabilistic model complements more targeted experimental approaches for elucidating the functional consequences of different viral mutations. We argue that running BVAS periodically as part of a real-time genomic surveillance program could provide valuable information for public health authorities about new lineages as they emerge.




Martin Jankowiak is a machine learning fellow at the Broad Institute of Harvard and MIT and a co-creator of the Pyro probabilistic programming framework. Martin has a PhD in theoretical physics from Stanford and works on a wide range of topics across probabilistic machine learning, bayesian inference, and applications in computational biology.