Author

Roberta Healey

University of CambridgePrimary ORCID profile (0009-0005-1460-2816 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Roberta HealeyiD1 paper · University of Leeds

Biology Disciplines

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Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:imaging· 1

Frequent Co-Authors

Adela Gaja Jezierska-Suwinska· 1 shared Andrea Díaz-Tendero Bravo· 1 shared Anika DammiD· 1 shared Beatrice Senatori· 1 shared Clément PellegriniD· 1 shared Gang SuniD· 1 shared George Harpum· 1 shared Ji ZhouiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperPathology

Adela Gaja Jezierska-Suwinska

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1 paper

Recent·Most cited

3D printing and deep learning enable holistic and dynamic analyses of tens of thousands of parasites infecting hundreds of genotypes

Siyuan Wei, Jie Zhou, Olaf Prosper Kranse, Unnati Sonawala, Gang Sun, Ziyang He, Beatrice Senatori, Clément Pellegrin, Andrea Díaz-Tendero Bravo, Roberta Healey, Victor Hugo Moura de Souza, Vincent C. T. Hanlon, George Harpum, Tithira Wijayathilake, Adela Gaja Jezierska-Suwinska, , Sebastian Eves‐van den Akker

This study uses 3D printing and deep learning to analyze parasite dynamics across hundreds of plant genotypes, identifying host genetic control of parasite traits and new QTLs.

bioRxiv · Aug 18, 2026 · PreprintPathology