Author

B. M. Stephens

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 3 Ecology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 4 Approach:experimental assay· 4 Organism:human· 4 Research Focus:cell type annotation· 3 Research Focus:gene regulatory network inference· 3 Assay:scRNA-seq· 3 Research Focus:clustering· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

A. Maitra· 4 shared P. A. Guerrero· 4 shared A. Semaan· 3 shared J. J. Lee· 3 shared V. Bernard· 3 shared C. M. Taniguchi· 2 shared J. Huang· 2 shared M. E. Monberg· 2 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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4 shared papersCancer Biology

A. Maitra

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Quantitative analysis of food web dynamics in a low export ecosystem

H. M. McNair, M. G. Meyer, S. J. Lerch, A. E. Maas, B. M. Stephens, J. Fox, K. N. Buck, S. M. Burns, I. Cetinic, M. R. Cohn, C. Durkin, S. M. Gifford, W. Gong, J. R. Graff, B. Jenkins, , T. A. Rynearson

The paper quantifies food web dynamics in a low export ecosystem, finding microbial recycling dominates carbon flow with minimal export due to slow turnover and high detrital background.

bioRxiv · Mar 17, 2023 · PreprintEcology

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype

V. Bahrambeigi, J. J. Lee, V. Branchi, J. T. Henry, K. I. Rajapakshe, B. M. Stephens, S. Dhebat, M. W. Hurd, R. Sun, P. Yang, W. Wang, S. E. Kopetz, A. Maitra, P. A. Guerrero, Z. Xu, , E. Ruppin

This study uses deep learning on plasma extracellular vesicle RNA to predict cancer subtypes, monitor treatment effects, and identify gene fusions and neoepitopes without tissue sampling.

bioRxiv · Oct 27, 2022Cancer Biology

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution.

M. E. Monberg, H. Geiger, R. Sharma, J. J. Lee, A. Semaan, V. Bernard, D. B. Swartzlander, B. M. Stephens, K. Chen, M. H. Katz, N. Robine, P. A. Guerrero, A. Maitra

This study reveals high intratumoral heterogeneity in pancreatic cancer cell lines and highlights issues with reproducibility and validity of preclinical models.

bioRxiv · Apr 13, 2021Cancer Biology

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

J. J. Lee, V. Bernard, A. Semaan, M. E. Monberg, J. Huang, B. M. Stephens, D. Lin, B. R. Weston, M. S. Bhutani, C. L. Haymaker, C. Bernatchez, C. M. Taniguchi, A. Maitra, P. A. Guerrero

This study uses scRNA-seq on pancreatic cancer biopsies to characterize tumor-stromal heterogeneity and ligand-receptor interactions, showing its utility over patient-derived organoids for precision oncology.

bioRxiv · Jul 28, 2020Cancer Biology

Single Cell Transcriptomics of Pancreatic Cancer Precursors Demonstrates Epithelial and Microenvironmental Heterogeneity as an Early Event in Neoplastic Progression

V. Bernard, A. Semaan, J. Huang, F. A. San Lucas, F. C. Mulu, B. M. Stephens, P. A. Guerrero, Y. Huang, J. Zhao, N. Kamyabi, S. Sen, P. A. Scheet, C. M. Taniguchi, M. P. Kim, C.-W. Tzeng, , H. A. Alvarez

This study uses single-cell RNA sequencing to analyze transcriptomic changes in pancreatic cancer precursors, revealing epithelial and microenvironmental heterogeneity during progression to cancer.

bioRxiv · Apr 26, 2018Pathology