PiSQRD: a web server for decomposing proteins into quasi-rigid dynamical domains. - Tyanko Aleksiev; Raffaello Potestio; Francesco Pontiggia; Stefano Cozzini; Cristian Micheletti (Bioinform., 2009)

ALADYN: a web server for aligning proteins by matching their large-scale motion. - Raffaello Potestio; Tyanko Aleksiev; Francesco Pontiggia; Stefano Cozzini; Cristian Micheletti (Nucleic Acids Res., 2010)

Knotted vs. Unknotted Proteins: Evidence of Knot-Promoting Loops. - Raffaello Potestio; Cristian Micheletti; Henri Orland (PLoS Comput. Biol., 2010)

Corresponding Functional Dynamics across the Hsp90 Chaperone Family: Insights from a Multiscale Analysis of MD Simulations. - Giulia Morra; Raffaello Potestio; Cristian Micheletti; Giorgio Colombo 001 (PLoS Comput. Biol., 2012)

Mechanical and Assembly Units of Viral Capsids Identified via Quasi-Rigid Domain Decomposition. - Guido Polles; Giuliana Indelicato; Raffaello Potestio; Paolo Cermelli; Reidun Twarock; Cristian Micheletti (PLoS Comput. Biol., 2013)

Computer Simulations of Soft Matter: Linking the Scales. - Raffaello Potestio; Christine Peter; Kurt Kremer (Entropy, 2014)

Fluctuations, Finite-Size Effects and the Thermodynamic Limit in Computer Simulations: Revisiting the Spatial Block Analysis Method. - Maziar Heidari; Kurt Kremer; Raffaello Potestio; Robinson Cortes-Huerto (Entropy, 2018)

Accelerating the identification of informative reduced representations of proteins with deep learning for graphs. - Federico Errica; Marco Giulini; Davide Bacciu; Roberto Menichetti; Alessio Micheli; Raffaello Potestio (CoRR, 2020)

Emergent circulation patterns from anonymized mobility data: Clustering Italy in the time of Covid. - Jules Morand; Shoichi Yip; Yannis Velegrakis; Gianluca Lattanzi; Raffaello Potestio; Luca Tubiana (CoRR, 2023)

Fast, Accurate, and System-Specific Variable-Resolution Modeling of Proteins. - Raffaele Fiorentini; Thomas Tarenzi; Raffaello Potestio (J. Chem. Inf. Model., 2023)

EXCOGITO, an Extensible Coarse-Graining Toolbox for the Investigation of Biomolecules by Means of Low-Resolution Representations. - Marco Giulini; Raffaele Fiorentini; Luca Tubiana; Raffaello Potestio; Roberto Menichetti (J. Chem. Inf. Model., 2024)

Density of states in neural networks: an in-depth exploration of learning in parameter space. - Margherita Mele; Roberto Menichetti; Alessandro Ingrosso; Raffaello Potestio (Trans. Mach. Learn. Res., 2025)