Francesco Petrizzelli

Dynamic consensus pocket detection across molecular dynamics ensembles reveals persistent and transient druggable sites

The paper evaluates pocket detection methods across molecular dynamics simulations to identify conserved and transient druggable sites in proteins.

NetMD: Unsupervised Synchronization of Molecular Dynamics Trajectories via Graph Embedding and Time Warping

NetMD synchronizes and analyzes molecular dynamics trajectories using graph embedding and time warping to reveal shared dynamics and deviations across conditions.

nAPOGEE: A machine-learning platform for clinically actionable pathogenicity assessment of all mitochondrial noncoding variants

nAPOGEE assesses pathogenicity of mitochondrial noncoding variants using machine learning, revealing consistent spatial correlation of predicted pathogenicity.

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

APOGEE 2 improves pathogenicity prediction for mitochondrial missense variants using a machine learning model based on ACMG/AMP guidelines and provides region-wise genome fragility assessments.

Investigating mitochondrial gene expression patterns in Drosophila melanogaster using network analysis to understand aging mechanisms

This study uses network analysis in Drosophila melanogaster to identify mitochondrial genes associated with aging and age-related diseases.

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

This study uses molecular dynamics and clinical data to show structural and dynamic differences between WTL and MBR SOD1 variants, linking these to distinct ALS clinical outcomes.