Author

Francesco Ceccarelli

University of CambridgeORCID 0000-0002-5995-5077Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Organism:human· 2 Assay:multiome· 2 Assay:spatial transcriptomics· 2 Research Focus:batch correction / integration· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1

Frequent Co-Authors

Julio Sáez-RodrígueziD· 2 shared Michele CeccarelliiD· 2 shared Sean B. HoldeniD· 2 shared Teresa NovielloiD· 2 shared Alberto ValdeolivasiD· 1 shared Alessia CovreiD· 1 shared Andrea AnichiniiD· 1 shared Anna Maria Di GiacomoiD· 1 shared

Activity by Year

2020-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Julio Sáez-RodríguezORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Transposable Elements and Homotypic Niches Drive Immune Dynamics and Resistance in Melanoma Epigenetic-based immunotherapy

Erika Ciervo, Francesco Ceccarelli, Anna Maria Di Giacomo, Piera Grisolia, Alessia Covre, Zein Mersini Besharat, Antonio De Falco, Francesca Pia Caruso, Luigi Laezza, Luigi Ferraro, Glòria Mas Martín, Daniel Bilbao, Siôn Llewelyn Williams, Benjamin Currall, Maria Fortunata Lofiego, , Michele Ceccarelli

This study identifies how epigenetic changes and spatial clustering influence immune dynamics and therapy resistance in melanoma through single-cell and spatial transcriptomics analyses.

Science Advances · Aug 7, 2026Peer-reviewedGenomics

Topography Aware Optimal Transport for Alignment of Spatial Omics Data

Francesco Ceccarelli, Pietro Liò, Julio Sáez-Rodríguez, Sean B. Holden, Jovan Tanevski

TOAST improves spatial omics data alignment by integrating spatial constraints into optimal transport, enhancing accuracy and biological interpretability.

Cell Reports Methods · Mar 30, 2026Peer-reviewedBioinformatics

OmniPath: integrated knowledgebase for multi-omics analysis

Dénes Türei, Jonathan Schaul, Nicolàs Palacio‐Escat, Balázs Bohár, Yunfan Bai, Francesco Ceccarelli, Elif Çevrim, Macabe Daley, Melih Darcan, Daniel Dimitrov, Tunca Doğan, Daniel Domingo‐Fernándéz, Aurélien J. F. Dugourd, Attila Gábor, Lejla Potari-Gul, , Julio Sáez-Rodríguez

OmniPath integrates molecular knowledge from 168 resources to support multi-omics analysis, offering curated data, predictions, and tools for causal modeling across bulk, single-cell, and spatial data.

Nucleic Acids Research · Nov 18, 2025Peer-reviewedBioinformatics

Deep learning approaches predict non-coding RNA functions from only raw sequence data

Teresa Noviello, Francesco Ceccarelli, Michele Ceccarelli, Luigi Cerulo

This study predicts non-coding RNA functions from raw sequence data using deep learning, achieving good accuracy without requiring secondary structure computation.

PLoS Computational Biology · Nov 11, 2020Peer-reviewedBioinformatics