Violeta Beleva Guthrie

This study evaluates machine learning methods for predicting peptide-MHC Class I binding affinities, finding that MHCnuggets performs similarly to existing methods but is faster and handles variable-length peptides.

This paper introduces a framework for inferring subclonal hierarchies in cancer using somatic mutations, demonstrating improved power and error control in multi-region tumor sequencing.