44 citations · 59 across the 4 of their papers we have counts for
4 papers
Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive
Kyle A. Beauchamp, Julie M. Behr, Ariën S. Rustenburg +3
Atomistic molecular simulations are a powerful way to make quantitative predictions, but the accuracy of these predictions depends entirely on the quality of the forcefield employe…
Efficient inference of protein structural ensembles
Thomas J. Lane, Christian R. Schwantes, Kyle A. Beauchamp +1
It is becoming clear that traditional, single-structure models of proteins are insufficient for understanding their biological function. Here, we outline one method for inferring,…
Probing the Origins of Two-State Folding
Thomas J. Lane, Christian R. Schwantes, Kyle A. Beauchamp +1
Many protein systems fold in a two-state manner. Random models, however, rarely display two-state kinetics and thus such behavior should not be accepted as a default. To date, many…
Why Can't We Predict RNA Structure At Atomic Resolution?
Kyle Beauchamp, Parin Sripakdeevong, Rhiju Das
No existing algorithm can start with arbitrary RNA sequences and return the precise, three-dimensional structures that ensures their biological function. This chapter outlines curr…