A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions.

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Bibliographic Details
Title: A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions.
Authors: Cao K; Broad Institute of MIT and Harvard, Cambridge, MA, United States., Li R; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States., Stražar M; Broad Institute of MIT and Harvard, Cambridge, MA, United States., Brown EM; Broad Institute of MIT and Harvard, Cambridge, MA, United States., Nguyen PNU; Broad Institute of MIT and Harvard, Cambridge, MA, United States., Pust MM; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States., Park J; Broad Institute of MIT and Harvard, Cambridge, MA, United States., Graham DB; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States., Ashenberg O; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, United States., Uhler C; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Massachusetts Institute of Technology, Cambridge, MA, United States., Xavier RJ; Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, United States.; Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Boston, MA, United States.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2026 Apr 11. Date of Electronic Publication: 2026 Apr 11.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.64898/2026.03.31.715361