Predicting high-fitness viral protein variants with Bayesian active learning and biophysics.

Abstract excerpt

The early detection of high-fitness viral variants is critical for pandemic response, yet limited experimental resources at the onset of variant emergence hinder effective identification. To address this, we introduce an active learning framework, VIRAL (Viral Identification via Rapid Active Learning), that integrates protein language model, Gaussian process with uncertainty estimation, and a biophysical model to...

Topics

• SARS-CoV-2
• Humans
• Bayes Theorem
• COVID-19
• Evolution, Molecular
• Mutation
• Spike Glycoprotein, Coronavirus