A. R. Atilgan

The paper develops stochastic programming methods to solve the Antibiotics Time Machine Problem under growth rate and transition probability uncertainties.

The paper uses community composition analysis from molecular dynamics simulations to study how point mutants and ligands affect PDZ3's binding dynamics and selectivity.

The paper generates artificial protein-like structures on a cubic lattice using simple rules and shows they closely resemble real globular proteins in structural descriptors.

This study investigates how mutations in the N-terminus of PDZ3 affect ligand binding selectivity through molecular dynamics simulations and free energy calculations.

The paper quantifies high-order epistasis in DHFR mutations under trimethoprim selection, revealing complex fitness landscapes and implications for inhibitor design.