Author

Stacy Wang

Baylor College of MedicineORCID 0009-0006-4155-5880Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:spatial transcriptomics· 2 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

Qian ZhuiD· 2 shared Akhila BalasubramanianiD· 1 shared Angela R. OmilianiD· 1 shared Arun SreekumariD· 1 shared Arundhati RaoiD· 1 shared Badrajee PiyarathnaiD· 1 shared Benjamin Strope· 1 shared Carolina GutiérreziD· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersBioinformatics

Qian ZhuORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintMar 3, 2026

CancerSTFormer enables multi-scale analysis of spot-resolution spatial transcriptomes and dissects the gene and immune regulatory responses of targeted therapies

Benjamin Strope, Dana Varghese, William Bowie…·Qian Zhu

CancerSTFormer analyzes spatial transcriptomes to study cancer niches and therapy responses at multiple scales.

DOI 10.64898/2025.12.22.696102

humanspatial transcriptomics

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Cancer BiologyNature CommunicationsPeer-reviewedJul 17, 2025

Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC

Qian Zhu, Akhila Balasubramanian, Jaya Ruth Asirvatham…·Arun Sreekumar

This study uses spatial omics to identify distinct tumor microenvironment profiles in Black and White American TNBC patients, linking them to different immunosuppressive mechanisms and clinical outcomes.

33 citationstop 1%

humanspatial transcriptomics

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BioinformaticsGenesPeer-reviewedJul 12, 2019

SCINA: Semi-Supervised Analysis of Single Cells in silico

Ze Zhang, Danni Luo, Xue Yun Zhong…·Tao Wang

SCINA is a semi-supervised model for analyzing scRNA-Seq and flow cytometry data, improving accuracy and efficiency over unsupervised methods by leveraging gene signatures.

288 citationstop 2%

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