Author

Mingcheng Li

University of California, San Francisco

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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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:proteomics· 1

Frequent Co-Authors

Abhilash BarpandaiD· 1 shared Amrik S. KangiD· 1 shared Anupam Anand OjhaiD· 1 shared Arun P. WiitaiD· 1 shared Benjamin J. HuangiD· 1 shared Beth Walker· 1 shared Caitlin E. CornelliD· 1 shared Clare Adams· 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 paperCancer Biology

Abhilash BarpandaORCID

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1 paper

Recent·Most cited

Deep Learning-based Modeling Enhances Efficacy of Natural Ligand CAR Binders Targeting CD70

Amrik S. Kang, Radhika Dalal, Mingcheng Li, Anupam Anand Ojha, Sujata B. Walunj, Caitlin E. Cornell, Ruyan Rahnama, Abhilash Barpanda, Sanjana Prudhvi, Trishna S. Patel, Mark Aspinall-O’Dea, Beth Walker, Clare Adams, Veronica Steri, Paul J. Phojanakong, , Arun P. Wiita

This study uses deep learning and physics-based modeling to engineer a CD27 variant that improves the efficacy of CD70-targeting CAR T-cells across multiple cancer models.

bioRxiv · Sep 10, 2026 · PreprintCancer Biology