Jesse Dylan Ziebarth

This paper introduces a framework to resolve conformational heterogeneity in human intrinsically disordered regions (IDRs) using polymer physics descriptors, revealing local and global structural differences linked to function.

The paper uses machine learning to analyze integrin expression patterns in cancer and metastasis, identifying key integrins that distinguish tissue types and disease states.

The paper develops predictive models for protein-protein binding affinity using amino acid composition at interfaces and identifies key amino acids that influence binding strength.

The paper examines how diet and genetics interact to affect longevity and weight gain in mice, finding that genetic differences significantly influence the impact of high-fat diets on lifespan.