Author

Chenxuan Zang

The University of Texas MD Anderson Cancer CenterORCID 0000-0001-5237-0351Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Organism:human· 2 Assay:spatial transcriptomics· 2 Approach:statistical model· 2 Assay:ATAC-seq· 1 Research Focus:clustering· 1

Frequent Co-Authors

Peng WeiiD· 3 shared Ziyi LiiD· 3 shared Charles Chuanhai GuoiD· 2 shared Alastair Mark ThompsoniD· 1 shared Allison M. AripoliiD· 1 shared Andrew K. GodwiniD· 1 shared Ashley I. HuppeiD· 1 shared Camron Smith· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Peng WeiORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cellular stemness identifies high-risk ductal carcinoma in situ and offers a therapeutic interception opportunity

Emily Schueddig, Veena Kochat, Emre Arslan, Y. Dallas, P. Yang, William Pedron, Z G Li, Reagan Henry, Jerome Lin, Mahinur Mattohti, Rashna Madan, Timothy A. Fields, S. Golem, S. A. Khan, Jamie Lynn Wagner, , Fariba Behbod

This study identifies stemness features in luminal hormone-responsive cells within DCIS that correlate with invasive progression and shows that targeting FOXA1 reduces tumor growth.

bioRxiv · May 16, 2026 · PreprintCancer Biology

TUSCAN: Tumor segmentation and classification analysis in spatial transcriptomics

Chenxuan Zang, Charles Chuanhai Guo, Yaohong Wang, Peng Wei, Z G Li

TUSCAN improves tumor region identification in spatial transcriptomics by integrating copy number variation profiles with histopathological images.

PLoS Computational Biology · Mar 17, 2026Peer-reviewedBioinformatics

A comparative study of statistical methods for identifying differentially expressed genes in spatial transcriptomics

Yishan Wang, Chenxuan Zang, Ziyi Li, Charles Chuanhai Guo, Dejian Lai, Peng Wei

This paper compares statistical methods for differential gene expression in spatial transcriptomics, finding that the GEE framework better controls false positives than the Wilcoxon test.

PLoS Computational Biology · Feb 11, 2026Peer-reviewedBioinformatics