Judith Gracia

This paper develops a Bayesian weighted scheme to predict SARS-CoV lineage evolution and demonstrates its retrospective application to anticipate SARS-CoV-2 emergence from SARS-CoV-1.

The paper presents a Python program that screens over a billion compounds from PubChem using machine learning to generate drug leads for Dengue and West Nile viruses, followed by automated In Silico modelling of their interactions with methyltransferase targets.

The paper introduces a programmatic tool that automates drug discovery for Hepatitis C virus using machine learning and molecular dynamics simulations to identify potential drug candidates.