239 citations · 497 across the 4 of their papers we have counts for
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q-bio.BM2023★ 6 cited
Navigating protein landscapes with a machine-learned transferable coarse-grained model
Nicholas E. Charron, Felix Musil, Andrea Guljas +18
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a uni…
q-bio.BM2018★ 54 cited
Simulations meet Machine Learning in Structural Biology
Adrià Pérez, Gerard Martínez-Rosell, Gianni De Fabritiis
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years, producing petabytes of simulation data at current force fiel…