MRC-University of Glasgow Centre for Virus Research

Computational Virology

We take a computational approach to the analysis of viruses integrating bioinformatics, mathematical modelling, computational biology, biostatistics, and machine learning/AI methods in our research.

Viruses evolve rapidly and pose ever-present threats to global health, making it essential to analyse their origins, evolution, and interactions with hosts. Statistical and machine learning methods facilitate the uncovering of key patterns and processes at multiple scales: genomic, structural, host-interaction, population, species, ecological and evolutionary.

In recent years deep learning models, originally developed to understand natural language, have been adapted to represent the “language” of viral genomes and proteins – allowing us to anticipate evolutionary change. This shift from hand-crafted features to data-driven representation learning and AI-based inference, marks a step-change in computational research, enabling insights critical for outbreak response, drug and vaccine discovery, and pandemic preparedness.

Please contact us if you’d be interested in working with us.