Author

Riccardo Roberto De Lucia

Human TechnopoleORCID 0000-0002-0885-1286Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:variant effect prediction· 3 Research Focus:benchmarking· 2 Approach:statistical model· 2 Assay:CRISPR screen· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Organism:human· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Francesco IorioiD· 3 shared Umberto PerroniD· 3 shared Alessandro VincetiiD· 2 shared Emre KarakoçiD· 2 shared Paolo CremaschiiD· 2 shared Alexandra LivanovaiD· 1 shared Andrea SottorivaiD· 1 shared Athanasios OikonomouiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersBioinformatics

Francesco IorioORCID

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3 papers

Recent·Most cited

CRISPR-enhanced assessment of variants of unknown significance nominates oncology therapeutic targets and drug repositioning opportunities

Aurora Savino, Athanasios Oikonomou, Francesca Perrone, Riccardo Roberto De Lucia, Letizia De Pietri, Yousra Belattar, Luke Brown, Miguel L. Grau, Katrina McCarten, Hanna Najgebauer, Umberto Perron, Luca Azzolin, Alexandra Livanova, Paolo Cremaschi, Núria López, , Francesco Iorio

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

bioRxiv · Sep 12, 2026 · PreprintBioinformatics

CRISPRcleanR WebApp: an interactive web application for processing genome-wide pooled CRISPR-Cas9 viability screen

Alessandro Vinceti, Riccardo Roberto De Lucia, Paolo Cremaschi, Umberto Perron, Emre Karakoç, Luca Mauri, Carlos Fernandez, Krzysztof Henryk Kluczynski, Daniel Stephen Anderson, Francesco Iorio

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

Cell Reports Methods · Jan 1, 2023Peer-reviewedBioinformatics

CoRe: A robustly benchmarked R package for the identification of core fitness genes in genome-wide pooled CRISPR knock-out screens

Alessandro Vinceti, Emre Karakoç, Clare Pacini, Umberto Perron, Riccardo Roberto De Lucia, Mathew J. Garnett, Francesco Iorio

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

BMC Genomics · Nov 17, 2021Peer-reviewedBioinformatics