Author

Andy T. Wang

National Institutes of Health

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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Bioinformatics· 1

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:imaging· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Antonios Papanicolau‐SengosiD· 1 shared Danh-Tai HoangiD· 1 shared Eldad David ShulmaniD· 1 shared Emma M. CampagnoloiD· 1 shared Eytan RuppiniD· 1 shared Kenneth AldapeiD· 1 shared MacLean P. NasrallahiD· 1 shared Ranjan Kumar BarmaniD· 1 shared

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2025-2025 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Antonios Papanicolau‐SengosORCID

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1 paper

Recent·Most cited

Pathologist-interpretable breast cancer subtyping and stratification from AI-inferred nuclear features

Ranjan Kumar Barman, Saugato Rahman Dhruba, Danh-Tai Hoang, Eldad David Shulman, Emma M. Campagnolo, Andy T. Wang, Stephanie A. Harmon, Tom C. Hu, Antonios Papanicolau‐Sengos, MacLean P. Nasrallah, Kenneth Aldape, Eytan Ruppin

This paper introduces EXPAND, an interpretable AI model that predicts breast cancer subtypes and survival using nuclear features, achieving performance comparable to black-box models.

bioRxiv · Sep 4, 2025 · PreprintBioinformatics