Author

Matt De Vries

Institute of Cancer ResearchORCID 0000-0002-4098-1611Unclaimed ORCID profile · follow to get notified of new preprints

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Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1

Frequent Co-Authors

Chris BakaliD· 2 shared Adam L. TysoniD· 1 shared Binghao ChaiiD· 1 shared Christopher W. DunsbyiD· 1 shared John Ciaran HutchinsoniD· 1 shared Leo Rowe-BrowniD· 1 shared Louis ChesleriD· 1 shared Lucas DentiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersCancer Biology

Chris BakalORCID

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2 papers

Recent·Most cited

Pheno-MYCN maps the morphological footprint of MYCN amplification in paediatric neuroblastoma

Binghao Chai, Olga Fourkioti, Reed Naidoo, Matt De Vries, Saira Waqar Ahmed, Thomas S. Jacques, Sally L. George, Louis Chesler, John Ciaran Hutchinson, Chris Bakal

Pheno-MYCN links slide-level MYCN prediction to interpretable morphological sub-populations in neuroblastoma, revealing a continuous gradient of MYCN-associated features.

bioRxiv · Oct 9, 2026 · PreprintCancer Biology

3D single-cell shape analysis using geometric deep learning

Matt De Vries, Lucas Dent, Nathan Curry, Leo Rowe-Brown, Vicky Bousgouni, Adam L. Tyson, Christopher W. Dunsby, Chris Bakal

The paper uses geometric deep learning to analyze 3D cell shapes from melanoma cells, identifying morphological signatures and predicting small molecule mechanisms.

bioRxiv · Jun 17, 2022 · PreprintBioinformatics