Pathogen genomic surveillance and the AI revolution

Authors: Lytras, Spyros ;

Lamb, Kieran D.;

Ito, Jumpei;

Grove, Joe ;

Yuan, Ke ;

Sato, Kei ;

Hughes, Joseph;

Robertson, David L.

Source: Journal of Virology

Full text

: https://doi.org/10.1128/jvi.01601-24

Abstract

The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the evolution of circulating viruses. Herein, we discuss how a state-of-the-art artificial intelligence approach called protein language models (pLMs) can be used for effectively analyzing pathogen genomic data. We highlight examples of pLMs applied to predicting viral properties and evolution and lay out a framework for integrating pLMs into genomic surveillance pipelines.

Rights

https://creativecommons.org/licenses/by/4.0/

Cite as

Lytras, S., Lamb, K., Ito, J., Grove, J., Yuan, K., Sato, K., Hughes, J. & Robertson, D. 2025, 'Pathogen genomic surveillance and the AI revolution', Journal of Virology, 99(2), article no: e01601-24. https://doi.org/10.1128/jvi.01601-24

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Identifiers

DOI: https://doi.org/10.1128/jvi.01601-24

Repository URI: https://eprints.gla.ac.uk/348054/