Kameron Bates

This paper uses AlphaFold 3 to predict T cell receptor antigen specificity from sequence, achieving high accuracy on unseen epitopes.

The paper introduces MHCIIFold-GNN, a method combining structural modeling and graph neural networks to predict CD4 T cell epitopes, achieving state-of-the-art performance.

The paper introduces the Myotonic Dystrophy Splice Index (SI) as a biomarker that correlates with muscle strength and mobility in DM1 patients.

The paper investigates the relationship between RNA mis-splicing and physical function in children with congenital myotonic dystrophy, finding significant correlations and predictive models.