Matthew K. Matlock

This paper establishes a standard operating procedure for manual refinement of somatic variants in tumor sequencing data to improve consistency and reproducibility.

This paper develops a deep learning model to classify glomeruli as normal or sclerotic in frozen kidney biopsy slides, achieving performance comparable to expert pathologists with limited training data.

This paper challenges the reliability of 'functional information' as a measure of evolutionary difficulty by showing that sequence alignment mutual information underestimates functional proteins and does not reflect functional proximity.