384 citations · 686 across the 9 of their papers we have counts for
9 papers
The Collective Burst Mechanism of Angular Jumps in Liquid Water
Adu Offei-Danso, Uriel N. Morzan, Alex Rodriguez +2
Understanding the microscopic origins of collective reorientational motions in aqueous systems requires techniques that allow us to reach beyond our chemical imagination. Herein, w…
DADApy: Distance-based Analysis of DAta-manifolds in Python
Aldo Glielmo, Iuri Macocco, Diego Doimo +6
DADApy is a python software package for analysing and characterising high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability…
High Dimensional Fluctuations in Liquid Water: Combining Chemical Intuition with Unsupervised Learning
Adu Offei-Danso, Ali Hassanali, Alex Rodriguez
The microscopic description of the local structure of water remains an open challenge. Here, we adopt an agnostic approach to understanding water's hydrogen bond network using data…
Intrinsic dimension of path integrals: data mining quantum criticality and emergent simplicity
Tiago Mendes-Santos, Adriano Angelone, Alex Rodriguez +2
Quantum many-body systems are characterized by patterns of correlations that define highly-non trivial manifolds when interpreted as data structures. Physical properties of phases…
Unsupervised learning universal critical behavior via the intrinsic dimension
T. Mendes-Santos, X. Turkeshi, M. Dalmonte +1
The identification of universal properties from minimally processed data sets is one goal of machine learning techniques applied to statistical physics. Here, we study how the mini…
The mechanism of RNA base fraying: molecular dynamics simulations analyzed with core-set Markov state models
Giovanni Pinamonti, Fabian Paul, Frank Noé +2
The process of RNA base fraying (i.e. the transient opening of the termini of a helix) is involved in many aspects of RNA dynamics. We here use molecular dynamics simulations and M…
Estimating the intrinsic dimension of datasets by a minimal neighborhood information
Elena Facco, Maria d'Errico, Alex Rodriguez +1
Analyzing large volumes of high-dimensional data is an issue of fundamental importance in data science, molecular simulations and beyond. Several approaches work on the assumption…
Automatic topography of high-dimensional data sets by non-parametric Density Peak clustering
Maria d'Errico, Elena Facco, Alessandro Laio +1
Data analysis in high-dimensional spaces aims at obtaining a synthetic description of a data set, revealing its main structure and its salient features. We here introduce an approa…
METAGUI 3: a graphical user interface for choosing the collective variables in molecular dynamics simulations
Toni Giorgino, Alessandro Laio, Alex Rodriguez
Molecular dynamics (MD) simulations allow the exploration of the phase space of biopolymers through the integration of equations of motion of their constituent atoms. The analysis…