Author

Elaine Huang

Oregon Health & Science UniversityORCID 0009-0002-3763-1095Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Elaine Huang1 paper · Boston University

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Organism:mouse· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

Amber HoffmaniD· 1 shared Aryn A. AlaniziiD· 1 shared Atiya MansooriD· 1 shared Brian S. HernandeziD· 1 shared Briana JohnsoniD· 1 shared Carol J. BultiD· 1 shared Charles KelleriD· 1 shared Daniel S. DerrickiD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperCancer Biology

Amber HoffmanORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Neoplastic immune mimicry potentiates breast tumor progression

Eric B. Berens, Sokchea Khou, Elaine Huang, Amber Hoffman, Briana Johnson, Nell C. Kirchberger, Shamilene Sivagnanam, Nicholas L. Calistri, Daniel S. Derrick, Tiera A. Liby, Ian C. McLean, Aryn A. Alanizi, Furkan Ozmen, Tugba Y. Ozmen, Gordon Brent Mills, , Lisa M. Coussens

This study identifies immune mimicry in breast cancer cells, where neoplastic cells express leukocyte receptors, enhancing tumor aggressiveness and therapy resistance.

Cancer Research · Oct 23, 2025Peer-reviewedCancer Biology

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

Noah Berlow, Rishi Raj Rikhi, Mathew N. Geltzeiler, Jinu Abraham, Matthew N. Svalina, Lara Emily Davis, Erin Wise, Maria Mancini, Jonathan Christopher Noujaim, Atiya Mansoor, Michael J. Quist, Kevin L. Matlock, Martin W. Goros, Brian S. Hernandez, Yee C. Doung, , Charles Keller

This paper develops a probabilistic model integrating sequencing and functional assay data to predict personalized drug combinations for sarcoma patients with exhausted treatment options.

BMC Cancer · Jun 17, 2019Peer-reviewedBioinformatics