Author

Joseph Goldfarb

Icahn School of Medicine at Mount Sinai

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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Systems Biology· 3

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Research Focus:differential expression· 3 Organism:human· 3 Approach:statistical model· 3 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

Ravi IyengariD· 3 shared Eric A. SobieiD· 2 shared Evren U. AzelogluiD· 2 shared Gomathi Jayaraman· 2 shared Iman TavassolyiD· 2 shared James M. GalloiD· 2 shared Jens HanseniD· 2 shared Pedro Martinez· 2 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersSystems Biology

Ravi IyengarORCID

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3 papers

Recent·Most cited

Multiscale mapping of transcriptomic signatures for cardiotoxic drugs

Jens Hansen, Yuguang Xiong, Mustafa M. Siddiq, Priyanka Dhanan, Bin Hu, Bhavana Shewale, Arjun Singh Yadaw, Gomathi Jayaraman, Rosa E. Tolentino, Yibang Chen, Pedro Martinez, Kristin G. Beaumont, Robert Sebra, Dušica Vidović, Stephan C. Schürer, , Ravi Iyengar

The paper identifies cardiotoxic drug signatures using bulk transcriptomics and integrates them with genomic and single-cell data to predict toxicity mechanisms.

Nature Communications · Sep 11, 2024Peer-reviewedSystems Biology

A tissue- and organ-based cell biological atlas of obesity-related human genes and cellular pathways

Iman Tavassoly, Valentina Barbieri, J. G. Coen van Hasselt, Pedro Martinez, Eric A. Sobie, Jens Hansen, Evren U. Azeloglu, Joseph Goldfarb, Philippe Sanséau, Deepak K. Rajpal, Ravi Iyengar

The paper constructs a tissue- and organ-based subcellular-function atlas of obesity-related genes and pathways using publicly available datasets and integration methods.

bioRxiv · Mar 16, 2020 · PreprintSystems Biology

Systems therapeutics analyses identify genomic signatures defining responsiveness to allopurinol and combination therapy for lung cancer

Iman Tavassoly, Yuan Hu, Shan Zhao, Chiara Mariottini, Aislyn D. W. Boran, Yibang Chen, Lisa Shi Yun Li, Rosa E. Tolentino, Gomathi Jayaraman, Joseph Goldfarb, James M. Gallo, Ravi Iyengar

The paper identifies genomic signatures predicting allopurinol and combination therapy responses in lung cancer using TCGA, CCLE, and patient-derived tumor data.

Molecular Oncology · May 22, 2019Peer-reviewedSystems Biology