3 papers
physics.comp-ph2020
Accelerating the identification of informative reduced representations of proteins with deep learning for graphs
Federico Errica, Marco Giulini, Davide Bacciu +3
The limits of molecular dynamics (MD) simulations of macromolecules are steadily pushed forward by the relentless developments of computer architectures and algorithms. This explos…
cond-mat.stat-mech2020
An information theory-based approach for optimal model reduction of biomolecules
Marco Giulini, Roberto Menichetti, M. Scott Shell +1
In the theoretical modelling of a physical system a crucial step consists in the identification of those degrees of freedom that enable a synthetic, yet informative representation…
cond-mat.soft2019
A deep learning approach to the structural analysis of proteins
Marco Giulini, Raffaello Potestio
Deep Learning (DL) algorithms hold great promise for applications in the field of computational biophysics. In fact, the vast amount of available molecular structures, as well as t…