Pathogen genomic surveillance and the AI revolution

作者：Spyros Lytras, Kieran D. Lamb, Jumpei Ito, Joe Grove, Ke Yuan, Kei Sato, Joseph Hughes, David L. Robertson · 发表于：Journal of Virology · 年份：2025 · DOI：10.1128/jvi.01601-24 · 被引用次数：14 · 研究领域：Genomics and Phylogenetic Studies、RNA and protein synthesis mechanisms、Machine Learning in Bioinformatics

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.