Fabio Anselmi

CONGAS+ is a Bayesian method that maps single-cell RNA and ATAC data to copy number clones, revealing subclonal architectures and genotype-phenotype relationships in cancer.

This study shows that robust deep learning models for object recognition rely on low spatial frequency information, as evidenced by their performance on adversarial attacks and common corruptions.

This paper introduces CNAqc, a toolset for validating clonal and subclonal copy number alterations in bulk tumor sequencing by addressing tumor purity, ploidy, and heterogeneity using simulations and single-cell data.