Youssef Lab

Research

Biology-first AI for virology

We work at the intersection of machine learning and evolutionary virology — building models that reason about how viral populations change over time, within a single host and across the globe.

Predicting Viral Evolution

Predicting how viruses evolve over time — from within-patient dynamics to long-term lineage forecasting to enable better treatments and preventions.

Designing Broadly Protective Vaccines

Using models of protein sequences and structures to guide the design of antigens and therapeutics that can hold up against future viral evolution, not just current strains.

People

Principal Investigator

Dr. Noor Youssef

Assistant Professor, Department of Molecular Genetics, University of Toronto

Noor received her PhD in Computational Biology and a BSc in Mathematics and Biology from Dalhousie University, and was previously Scientific Lead of Predictive Modelling at the Marks Lab, Harvard Medical School.

Lab Members

The lab is just getting started at the University of Toronto. If you are interested in joining, contact Dr. Youssef (n.youssef@utoronto.ca).

Publications

A full and up-to-date list of publications is available on Google Scholar.

Machine learning reveals hidden dimensions of functional similarity

Youssef N, Gurev S, Marks DS · PNAS (Invited Commentary) · 2026
Variant effect prediction with reliability estimation across priority viruses

Gurev S, Youssef N (co-first), Jain N, Marks DS · Nature Methods · 2025
Computationally designed proteins mimic antibody immune evasion in viral evolution

Youssef N, Gurev S, Ghantous F, Brock K, Jaimes JA, Dauphin A, Yurkovetskiy L, Soto D, Estanboulieh R, Kotzen B, Bosso M, Lemieux J, Luban J, Seaman MS, Marks DS · Immunity, Vol. 58 · 2025
Deep mutational scanning of HBV reveals a mechanism for cis-preferential reverse transcription

Yu Y, Kass MA, Zhang M, Youssef N, Freije CA, Brock KP, Seifert LL, Venkittu S, Hong X, Shlomai A, de Jong YP, Marks DS, Rice CM, Schneider WM · Cell, Vol. 187 · 2024
Learning from pre-pandemic data to forecast viral antibody escape

Thadani NT, Gurev S, Notin P, Youssef N, Rollins NJ, Sander CA, Gal Y, Marks D · Nature, Vol. 622 · 2023
Evolution of amino acid propensities under stability-mediated epistasis

Youssef N, Susko E, Roger A, Bielawski JP · Molecular Biology and Evolution, Vol. 39(3) · 2022
Shifts in amino acid preferences as proteins evolve: a synthesis of experimental and theoretical work

Youssef N, Susko E, Roger A, Bielawski JP · Protein Science, Vol. 30(10) · 2021
Expanding the search for sperm transmission elements in the mitochondrial genomes of bivalve mollusks

Stewart DT, Robicheau BM, Youssef N, Garrido-Ramos MA, Chase EE, Breton S · Genes, Vol. 12(8) · 2021
Consequences of stability-induced epistasis for substitution rates

Youssef N, Susko E, Bielawski JP · Molecular Biology and Evolution, Vol. 37(11) · 2020
A phenotype–genotype codon model for detecting adaptive evolution

Jones CT, Youssef N, Susko E, Bielawski JP · Systematic Biology, Vol. 69(4) · 2020
An unusual evolutionary strategy: the origins, genetic repertoire, and implications of doubly uniparental inheritance of mitochondrial DNA in bivalves

Stewart DT, Breton S, Chase EE, Robicheau BM, Bettinazzi S, Pante E, Youssef N, Garrido-Ramos MA · Evolutionary Biology — A Transdisciplinary Approach (Springer) · 2020
Introduction to genome biology and diversity

Youssef N, Budd A, Bielawski JP · Evolutionary Genomics, Methods in Molecular Biology, Vol. 1910 (Humana) · 2019
Phenomenological load on model parameters can lead to false biological conclusions

Jones CT, Youssef N, Susko E, Bielawski JP · Molecular Biology and Evolution, Vol. 35 · 2018
Shifting balance on a static mutation-selection landscape: a novel scenario of positive selection

Jones CT, Youssef N, Susko E, Bielawski JP · Molecular Biology and Evolution, Vol. 34 · 2017

Computational and AI models to help us predict, prepare for, and prevent viral outbreaks.