Alessandro Arduini

Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender

CellBender removes systematic background noise from droplet-based single-cell data using a deep generative model, improving alignment with established gene expression patterns.

TAILS identifies candidate substrates and biomarkers of ADAMTS7, a therapeutic protease target in coronary artery disease

The paper identifies ADAMTS7 substrates and cleavage sites using TAILS, revealing potential biomarkers for coronary artery disease.

Deep learning enables genetic analysis of the human thoracic aorta

This study uses deep learning to analyze aortic dimensions from MRI and identifies genetic loci associated with aortic diameter, highlighting SVIL as a key gene and developing a polygenic score for aneurysm risk.

Transcriptional and Cellular Diversity of the Human Heart

The paper uses single-nucleus RNA sequencing to define the transcriptional and cellular diversity of the non-failing human heart, identifying 9 major cell types and 20 subclusters.