This project is aimed at unraveling the intricacies of viral transmission and immune protection, with a primary focus on the human cytomegalovirus (CMV). This endeavor, rooted in cutting-edge machine learning (ML), is driven by the imperative to inform vaccine design and public health strategies against novel and re-emerging viruses.
The team will capitalize on ongoing collaborations, which pioneered ML techniques for characterizing SARS-CoV-2 diversity. Building on this foundation, the project team will focus its expertise towards decoding CMV’s pathogenesis and transmission patterns. CMV’s significance cannot be overstated – a widespread yet understudied virus responsible for congenital infections and childhood disabilities worldwide.
The team’s approach involves harnessing the power of next-generation sequencing and clinical data to shed light on CMV’s genetic heterogeneity. The team has developed novel ML tools uniquely suited to decipher the intricacies of CMV’s genomic makeup. Additionally, they have crafted a groundbreaking “CMV-Scan” assay, capable of providing a view of viral variant-specific antibodies to dissect CMV reinfection dynamics.
The immediate goals of this project encompass refining ML tools for comprehensive mutational analysis, utilizing CMV-Scan data to dissect reinfection phenomena, unearthing critical genotypic features for next-generation vaccines, and extending these insights to address other global viral threats.