Author

Maria-Grazia Molvetti

University of Zurich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 1

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Andreas DzungiD· 1 shared Andreja Jovic· 1 shared Christian Corona· 1 shared Cyril Y. RamathaliD· 1 shared Evelyn LattmanniD· 1 shared Kiran Saini· 1 shared Manisha Ray· 1 shared Matt Barnes· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperCancer Biology

Andreas DzungORCID

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Author profile →

1 paper

Recent·Most cited

Deep learning-driven morphology analysis enables label-free classification of therapeutic agent- naive versus resistant cancer cells

Cyril Y. Ramathal, Kiran Saini, Zhouyang Lian, Christian Corona, Tiffine Pham, Ryan Carelli, Stéphane C. Boutet, Manisha Ray, Sunantha Sethuraman, Vivian Prindle, Evelyn Lattmann, Maria-Grazia Molvetti, Andreas Dzung, Mitchell Paul Levesque, Matt Barnes, Andreja Jovic

This study uses deep learning to classify drug-naive and resistant cancer cells based on morphology, achieving high accuracy across multiple cancer types and drug classes.

bioRxiv · Jan 22, 2025 · PreprintCancer Biology