Author

Aditya Udupa

Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720;

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

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Synthetic Biology· 1

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Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Organism:yeast· 1

Frequent Co-Authors

Angelica W. Y. Lam· 1 shared Claire J. LeBlanc· 1 shared Daniel Aguilera· 1 shared Gean Hu· 1 shared Izaiah Ornelas· 1 shared James K. Nunez· 1 shared Liam D. KirkpatrickiD· 1 shared Lucia C. Strader· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperSynthetic Biology

Angelica W. Y. Lam

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1 paper

Recent·Most cited

Machine learning guided design of strong transcriptional activation domains

Marissa A. Zintel, Claire J. LeBlanc, Sanjana R. Kotha, Melvin Soriano, Rishaan J. Bansal, Daniel Aguilera, Touss Majidi, Izaiah Ornelas, Liam D. Kirkpatrick, Aditya Udupa, Gean Hu, Pooja Agarwal, Angelica W. Y. Lam, James K. Nunez, Patrick M. Shih, , Max V. Staller

The paper designs functional transcriptional activation domains using machine learning and experimental validation, finding that over 90% of predicted sequences work in yeast.

bioRxiv · Nov 2, 2026 · PreprintSynthetic Biology