Harnessing Computational Genomics for Predicting Viral Evolution

Watch a 35-minute conference talk from the Computational Genomics Summer Institute where Dr. Pavel Skums explores cutting-edge approaches in computational genomics for predicting viral evolution. Delve into advanced research methodologies that combine network analysis, mutation tracking, and evolutionary patterns to forecast emerging viral variants. Learn about groundbreaking studies in viral genomics, including early detection systems for viral variants through coordinated substitution networks, quantitative analysis of HCV populations, prediction of SARS-CoV-2 mutations, and the application of machine learning to understand viral evolution and escape mechanisms. Gain insights into how computational tools and large-scale genomic data analysis are revolutionizing our ability to anticipate and respond to viral threats.