Harry M. Scholes

The paper uses phenomics and machine learning to predict protein functions in fission yeast, identifying novel roles and validating predictions through experimental validation.

The paper introduces FunSite, a machine learning method for predicting functional sites in proteins using sequence, structure, and evolutionary data from CATH functional families, showing superior performance over existing methods.

The paper predicts SARS-CoV-2 spike protein interactions with ACE2 orthologues across 215 vertebrates, finds mutations in ACE2 are more detrimental, and shows human strains are present in animals.