Author

Alice Wang

University of PennsylvaniaPrimary ORCID profile (0000-0003-4468-9367 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Alice WangiD1 paper · Cold Spring Harbor Laboratory

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:genetic perturbation / CRISPR· 1 Organism:human· 1

Frequent Co-Authors

Ágnes HolczbaueriD· 1 shared Andrew McDavidiD· 1 shared Ben Z. StangeriD· 1 shared Constantinos KoumenisiD· 1 shared Crystal S. ConniD· 1 shared Daniel P. BeitingiD· 1 shared Erik Nash· 1 shared Greg FinakiD· 1 shared

Activity by Year

2014-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

Ágnes HolczbauerORCID

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2 papers

Recent·Most cited

SPTBN2 promotes an immunosuppressive tumor microenvironment and cross-resistance to anti-cancer therapies

Quoc Thang Bui, Raghavendra Basavaraja, Mayura R. Dhamdhere, Ágnes Holczbauer, Luca Paruzzo, Puneeth Guruprasad, Michael Scaglione, Yingying Tang, Yu Sun, Daniel P. Beiting, Erik Nash, Hossein Fazelinia, Lynn A. Spruce, Alice Wang, Kai Tan, , Serge Yu. Fuchs

This study identifies SPTBN2 as a regulator of immunosuppressive tumor microenvironment and cross-resistance to therapies, showing its role in suppressing CAR T-cell efficacy.

bioRxiv · Apr 1, 2026 · PreprintCancer Biology

Modeling bi-modality improves characterization of cell cycle on gene expression in single cells

Lucas Dennis, Andrew McDavid, Patrick Danaher, Greg Finak, Michael Krouse, Alice Wang, Philippa Webster, Joseph Beechem, Raphael Gottardo

The paper models bi-modality in single-cell gene expression to improve characterization of cell cycle effects and finds the cell cycle explains 5%-17% of expression variability.

PLoS Computational Biology · Jul 17, 2014Peer-reviewedBioinformatics