21 citations · 35 across the 5 of their papers we have counts for
6 papers
EXCOGITO, an extensible coarse-graining toolbox for the investigation of biomolecules by means of low-resolution representation
Marco Giulini, Raffaele Fiorentini, Luca Tubiana +2
Bottom-up coarse-grained (CG) models proved to be essential to complement and sometimes even replace all-atom representations of soft matter systems and biological macromolecules.…
Making sense of complex systems through resolution, relevance, and mapping entropy
Roi Holtzman, Marco Giulini, Raffaello Potestio
Complex systems are characterised by a tight, nontrivial interplay of their constituents, which gives rise to a multi-scale spectrum of emergent properties. In this scenario, it is…
A mapping space Odyssey: characterising the statistical and metric properties of reduced representations of macromolecules
Roberto Menichetti, Marco Giulini, Raffaello Potestio
Simplified representations of macromolecules help in rationalising and understanding the outcome of atomistic simulations, and serve to the construction of effective, coarse-graine…
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…
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…
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…