Ken A. Dill

The paper proposes a model showing how nucleic acids and proteins could have cooperatively bootstrapped each other to achieve autocatalytic functionality at the origins of life.

This study combines normal modes with weighted ensemble simulations to generate unbiased protein pathways efficiently.

The paper defines brain integration and segregation using the Ising model to analyze functional MRI data, finding that these states become less balanced with age.

The paper fine-tunes AlphaFold using high-resolution MHC-peptide crystal structures to improve prediction accuracy for MHC-peptide complex structures, outperforming existing methods in RMSD and lDDT scores.

The paper develops a computational model to predict how excipients affect protein-protein affinities by combining MD simulations and thermodynamic theory.

The paper uses percolation theory to analyze brain development, finding that early white matter tracts become longest and densest, maintaining a giant cluster across aging and disease.

This study shows that aging reduces brain network synchrony, modeled as a critical point in communication strength, and demonstrates that metabolic changes can drive these global shifts.