Author

Omar Darwiche Domingues

ORCID 0000-0002-7455-348XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:spatial transcriptomics· 2 Research Focus:batch correction / integration· 1 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Approach:statistical model· 1

Frequent Co-Authors

Vincent CabeliiD· 2 shared Alberto RomagnoniiD· 1 shared Alexandra HardyiD· 1 shared Andre L. MoreiraiD· 1 shared Arthur Pignet· 1 shared Aurélie SwalduziD· 1 shared Benoît SchmauchiD· 1 shared Brooke E. HowittiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersCancer Biology

Vincent CabeliORCID

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2 papers

Recent·Most cited

Comprehensive benchmarking of batch integration methods for spatial transcriptomics using a large-scale cancer atlas

Liam Ludington, Khalil Ouardini, Xavier Sécheresse, Régis Loeb, Arthur Pignet, Omar Darwiche Domingues, Vincent Cabeli

This study benchmarks batch integration methods for spatial transcriptomics using a cancer atlas, finding probabilistic methods excel in batch correction while graph-based methods perform better in spatial conservation.

bioRxiv · Jan 13, 2026 · PreprintCancer Biology

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

Benoît Schmauch, Vincent Cabeli, Omar Darwiche Domingues, Jean-Eudes Le Douget, Alexandra Hardy, Reda Belbahri, Charles Maussion, Alberto Romagnoni, Markus Eckstein, Florian Siegfried Fuchs, Aurélie Swalduz, Sylvie Lantuéjoul, Hugo Crochet, François Ghiringhelli, Valentin Dérangère, , Matteo Cesaroni

This study uses deep learning to predict YAP1/TEAD activity from histology slides, linking histological patterns to disease aggressiveness in cancer patients.

iScience · Dec 20, 2024Peer-reviewedBioinformatics