Author

Penghui Yang

Yale UniversityORCID 0000-0002-3131-1982Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Organism:human· 3 Research Focus:spatial domain detection· 2 Assay:spatial transcriptomics· 2 Approach:transformer / foundation model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:clustering· 1

Frequent Co-Authors

Xiang ZhouiD· 3 shared Jade Xiaoqing WangiD· 2 shared Siyu HouiD· 2 shared Anagha TapaswiiD· 1 shared Hui Song WaniD· 1 shared Hui Wan· 1 shared Jenna L MilleriD· 1 shared Jesse W. WotringiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersBioinformatics

Xiang ZhouORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Exposure to p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) Perturbs Cell State and Stem Cell Markers and Induces an Epidermal Phenotype in Human Breast Cells

Jenna L Miller, Anagha Tapaswi, Jesse W. Wotring, Katelyn M. Polemi, Penghui Yang, Xiang Zhou, Laurie Kathleen Svoboda, Jonathan Z. Sexton, Justin A. Colacino

This study shows that DDE exposure alters cell state and stem cell markers in breast cells, inducing an epidermal phenotype and upregulating keratinization pathways.

bioRxiv · Oct 20, 2026 · PreprintPharmacology & Toxicology

SVC: A Vision Transformer-based Spatially and Virtually Embedded Cell Model for Deciphering Subcellular Spatial Transcriptomic Heterogeneity

Hui Song Wan, Penghui Yang, Siyu Hou, Jade Xiaoqing Wang, Xiang Zhou

SVC predicts subcellular transcript localization and co-organization using a Vision Transformer model, revealing disease patterns and spatial biology not accessible at the cell level.

bioRxiv · Oct 14, 2026 · PreprintBioinformatics

Accessible and reproducible deployment reveals the practical boundaries of single-cell foundation models

Siyu Hou, Penghui Yang, Wenjing Ma, Jinxi Xiang, Jade Xiaoqing Wang, Hui Wan, Ying Ma, Xiang Zhou

Across 13 single-cell foundation models and 94 datasets, PCA and established methods usually match or beat them; pretrained embeddings help mainly with scarce labels, rare cells and open-set detection.

bioRxiv · Sep 2, 2026 · PreprintBioinformatics✦ In-depth digest