Author

A. R. Tannenbaum

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· 5 Bioengineering· 1

Signature Assays, Organisms & Methods

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Organism:human· 5 Approach:statistical model· 5 Assay:bulk RNA-seq· 4 Approach:deep learning· 4 Research Focus:differential expression· 3 Research Focus:cell type annotation· 2 Research Focus:drug response / drug discovery· 2 Research Focus:gene regulatory network inference· 2

Frequent Co-Authors

J. H. Oh· 3 shared J. O. Deasy· 3 shared L. Norton· 3 shared J. Zhu· 2 shared A. Carpio· 1 shared A. J. Levine· 1 shared A. K. Simhal· 1 shared B. Weigelt· 1 shared

Activity by Year

2017-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersCancer Biology

J. H. Oh

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Author profile →

6 papers

Recent·Most cited

Functional transcriptional signatures for tumor-type-agnostic phenotype prediction

C. Weistuch, K. A. Murgas, J. Zhu, L. Norton, K. A. Dill, A. R. Tannenbaum, J. O. Deasy

The paper identifies six transcriptomic archetypes from normal tissues that correlate with cancer patient survival and drug sensitivity, suggesting cancer adopts normal tissue transcriptional features.

bioRxiv · Apr 12, 2023 · PreprintCancer Biology

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival

A. K. Simhal, K. H. Maclachlan, R. H. Elkin, J. Zhu, L. Norton, J. O. Deasy, J. H. Oh, S. Z. Usmani, A. R. Tannenbaum

This study uses gene interaction network analysis in multiple myeloma to identify immune-related genes associated with shorter survival.

bioRxiv · Apr 5, 2023Cancer Biology

Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint Inhibitors

R. Elkin, J. H. Oh, Y. L. Liu, P. Selenica, B. Weigelt, J. S. Reis-Filho, D. Zamarin, J. O. Deasy, L. Norton, A. J. Levine, A. R. Tannenbaum

This paper introduces a network curvature-based method to predict prognosis in high-grade serous ovarian cancer patients treated with immune checkpoint inhibitors using copy number alterations.

bioRxiv · Jun 10, 2021Cancer Biology

ImPartial: Partial Annotations for Cell Instance Segmentation

N. Martinez, G. Sapiro, A. R. Tannenbaum, T. J. Hollmann, S. Nadeem

ImPartial improves cell instance segmentation in noisy multiplex spatial images using partial annotations and self-supervised imputation, showing effectiveness on cancer datasets.

bioRxiv · Jan 20, 2021 · PreprintBioengineering

Fingerprints of cancer by persistent homology

A. Carpio, L. L. Bonilla, J. C. Mathews, A. R. Tannenbaum

The paper uses topological data analysis to identify cancer-specific patterns in gene expression by analyzing persistence barcodes and Betti numbers across different cancer types.

bioRxiv · Sep 23, 2019 · PreprintCancer Biology

Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach

M. Pouryahya, J. H. Oh, J. Mathews, J. Deasy, A. R. Tannenbaum

The paper uses a geometric network approach to analyze drug response in cancer cell lines, linking network robustness to drug sensitivity and identifying genomic biomarkers.

bioRxiv · Nov 22, 2017Cancer Biology