6 papers
Investigating causality between principal components in protein dynamics
Debarshi Banerjee, Ali Hassanali, Alessandro Laio
Principal component analysis (PCA) is widely used to characterize collective protein motions from molecular dynamics (MD) simulations. While PCA identifies the dominant modes of st…
Causality in Liquid Water as a Hallmark of Emergent Glassy Dynamics
Leon Huet, Vittorio Del Tatto, Debarshi Banerjee +2
In molecular liquids such as water, time-delayed influences between microscopic or mesoscopic variables are typically probed using time-correlation functions, which are symmetric u…
Phase Transitions in Unsupervised Feature Selection
Jonathan Fiorentino, Michele Monti, Dimitrios Miltiadis-Vrachnos +3
Identifying minimal and informative feature sets is a central challenge in data analysis, particularly when few data points are available. Here we present a theoretical analysis of…
Linear scaling causal discovery from high-dimensional time series by dynamical community detection
Matteo Allione, Vittorio Del Tatto, Alessandro Laio
Understanding which parts of a dynamical system cause each other is extremely relevant in fundamental and applied sciences. However, inferring causal links from observational data,…
Towards a robust approach to infer causality in molecular systems satisfying detailed balance
Vittorio Del Tatto, Debarshi Banerjee, Ali Hassanali +1
The ability to distinguish between correlation and causation of variables in molecular systems remains an interesting and open area of investigation. In this work, we probe causali…
Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance
Romina Wild, Felix Wodaczek, Vittorio Del Tatto +2
Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified…