Umberto Perron

CRISPR-VUS identifies rare variants linked to gene dependency in cancer cell lines, prioritizing potential drivers and therapeutic targets through functional validation.

The paper trains an ensemble classifier to predict cetuximab sensitivity in colorectal cancer PDXs using multi-omic data, achieving high accuracy and demonstrating its utility for therapeutic biomarker development.

CRISPRcleanRWebApp is a web tool that processes CRISPR-Cas9 viability screens to reduce false positives by correcting biases in gene targeting.

The paper develops a computational framework to create reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 screens, improving efficiency without compromising results.

CoRe identifies core-fitness genes from CRISPR-Cas9 screens, outperforming existing tools and providing more reliable results.