Author

J. O. Deasy

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 Biophysics· 1

Signature Assays, Organisms & Methods

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Organism:human· 5 Approach:statistical model· 5 Research Focus:differential expression· 4 Assay:bulk RNA-seq· 3 Research Focus:cell type annotation· 3 Research Focus:gene regulatory network inference· 3 Approach:deep learning· 2 Research Focus:benchmarking· 1

Frequent Co-Authors

A. R. Tannenbaum· 3 shared J. H. Oh· 3 shared L. Norton· 3 shared A. J. Levine· 2 shared A. Tannenbaum· 2 shared C. Weistuch· 2 shared J. Zhu· 2 shared K. A. Murgas· 2 shared

Activity by Year

2019-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersCancer Biology

A. R. Tannenbaum

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Author profile →

6 papers

Recent·Most cited

Mapping the Single-cell Differentiation Landscape of Osteosarcoma

D. D. Truong, C. Weistuch, K. A. Murgas, P. Admane, B. L. King, J. Chauviere Lee, S.-E. Lamhamedi-Cherradi, J. Swaminathan, N. C. Daw, N. Gordon, V. Gopalakrishnan, R. G. Gorlick, N. Somaiah, J. O. Deasy, A. G. Mikos, , J. Ludwig

The paper maps the differentiation landscape of osteosarcoma using single-cell data to identify gene modules linked to cell fate and patient survival.

bioRxiv · Sep 13, 2023Cancer Biology

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

Anatomically Informed 3D Printed CT phantoms: The First Step of a Pipeline To Identify Robust Quantitative Radiomic Features

U. Mahmood, A. Apte, C. Kanan, D. Bates, G. Corrias, L. Mannelli, J. H. Oh, Y. E. Erdi, J. Nguyen, J. O. Deasy, A. S. Dave

This paper demonstrates the feasibility of creating 3D printed CT phantoms from patient data to assess the repeatability and robustness of radiomic features across different scanning parameters.

bioRxiv · Sep 18, 2019 · PreprintBiophysics

Robust and Interpretable PAM50 Reclassification Exhibits Survival Advantage for Myoepithelial and Immune Phenotypes

J. Mathews, S. Nadeem, A. J. Levine, M. Pouryahya, J. O. Deasy, A. Tannenbaum

The paper reclassifies breast tumors into 7 classes using interpretable mRNA signatures, showing improved survival outcomes for myoepithelial and immune-related phenotypes.

bioRxiv · Jul 16, 2019Cancer Biology