معرفی
John Barton, PhD, is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research integrates statistical physics, machine learning, and population genetics to study viral evolution and immunity, with a focus on HIV and SARS-CoV-2. His lab develops computational tools like popDMS for analyzing viral fitness landscapes and has contributed to understanding mechanisms of viral escape from immune responses and vaccine design strategies.
Education:
- PhD in Physics from Rutgers University
Research Interests: Barton’s work addresses fundamental questions about viral adaptation, clonal heterogeneity in viral reservoirs, and the interplay between chronic infections and evolutionary dynamics. He applies advanced mathematical frameworks such as Ising/Potts models and covariance factorization to decode genetic data from large-scale surveillance efforts.
Key Contributions: Recent studies include modeling SARS-CoV-2 transmission via genomic data, analyzing HIV evolutionary trajectories in humans and macaques, and developing methods to infer mutation effects from deep mutational scans. His lab also explores innate immune adaptation and the design of broadly neutralizing antibody-based therapies.
Awards & Recognition: No specific awards listed, though his work has been supported by NIH-funded initiatives in computational virology.
Labs/Teams: Leads the Barton Lab, part of the School of Medicine’s Computational and Systems Biology program, collaborating with global networks in infectious disease research and public health.
