Deep learning multi-omics integration identifies new molecular subtypes of lung cancer.

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Bibliographic Details
Title: Deep learning multi-omics integration identifies new molecular subtypes of lung cancer.
Authors: Gonda B; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA., Wang D; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA., Azim SM; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA., Romano G; Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA, USA.; Immune Cell Regulation & Targeting Program, Sidney Kimmel Comprehensive Cancer Center, Philadelphia, PA, USA., Dehzangi I; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA. i.dehzangi@rutgers.edu.; Department of Computer Science, Rutgers University, Camden, NJ, USA. i.dehzangi@rutgers.edu.; Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, 08901, USA. i.dehzangi@rutgers.edu.
Source: BioData mining [BioData Min] 2026 May 21; Vol. 19 (1). Date of Electronic Publication: 2026 May 21.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1756-0381
DOI:10.1186/s13040-026-00563-z