Identifying condition-related cell-cell communication events using supervised tensor analysis.

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Bibliographic Details
Title: Identifying condition-related cell-cell communication events using supervised tensor analysis.
Authors: Dai Q; Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA 30322, USA; Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA., Yang J; Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA. Electronic address: jingjing.yang@emory.edu., Epstein MP; Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA. Electronic address: mpepste@emory.edu.
Source: American journal of human genetics [Am J Hum Genet] 2026 Jul 02; Vol. 113 (7), pp. 1495-1508. Date of Electronic Publication: 2026 Jun 04.
Publication Type: Journal Article
Journal Info: Publisher: Cell Press Country of Publication: United States NLM ID: 0370475 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1537-6605 (Electronic) Linking ISSN: 00029297 NLM ISO Abbreviation: Am J Hum Genet Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1537-6605
DOI:10.1016/j.ajhg.2026.05.005