Tommaso Mazza

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

STRmie-HD is a tool for high-resolution genotyping of HTT repeat expansions and somatic mosaicism across sequencing platforms, capturing interruptions and rare variants with high sensitivity.

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

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

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.

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

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.

The paper performs an integrative CUT&Tag/RNA-Seq analysis to investigate how macroH2A1 histone variants influence iPSC reprogramming efficiency in human cells.

The paper analyzes mouse genome data to show ultradian genes are more evolutionarily conserved and linked to dawn/dusk transitions.