NCMBM International Seminar: Jonathan Frazer

NCMBM, as part of its International Seminar series, will be welcoming Jonathan Frazer, Group Leader at the Centre for Genomic Regulation (CRG) in Barcelona, Spain. 

His talk is entitled:"Reading evolutionary constraint with deep learning: from rare disease to endangered species".

Graphical representation of DNA in blue tones.

About the speaker

Portrait of Jonathan Frazer (man wearing glasses).

Jonathan Frazer is a Group Leader at the Centre for Genomic Regulation (CRG) in Barcelona, where he co-leads the Probabilistic Machine Learning and Genomics Group with Mafalda Dias. His lab's research sits at the intersection of deep learning, evolutionary genomics, and clinical genetics, with a focus on method development for diagnosis and preventative care.

Abstract

Deep learning models trained on the genetic variation seen across life on Earth provide a unique opportunity to learn about ultra rare variants. By identifying constraint patterns on large evolutionary timescales, these models provide valuable information about which rare variants are likely to be benign and which are likely to give rise to disease. While there has been considerable progress on this front in recent years, and these models are now a standard component of diagnostic pipelines, it seems clear that both our understanding of how to build useful models, and how to make effective use of such models, is still in its infancy. 

In this talk I’ll review recent successes and failures in developing deep learning models for learning about the genetic underpinnings of rare disease, first steps in developing similar models for endangered species, and what these species can teach us about lethal variants.

About the seminar series

Once a month, NCMBM invites international guest speakers to present on topics within molecular life science and medicine.

The seminar is open to all, with no registration needed.

Tea, coffee and a simple lunch will be served at 11.30 before the seminar.

Published Apr. 21, 2026 2:39 PM - Last modified Apr. 23, 2026 2:05 PM