A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features.

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Title: A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features.
Authors: Carnevali D; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain., Zhong L; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China., González-Almela E; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China., Viana C; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain., Rotkevich M; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain., Wang A; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China., Franco-Barranco D; Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), Paseo Manuel Lardizabal 1, San Sebastian, Spain.; Donostia International Physics Center (DIPC), San Sebastian, Spain., Gonzalez-Marfil A; Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), Paseo Manuel Lardizabal 1, San Sebastian, Spain.; Donostia International Physics Center (DIPC), San Sebastian, Spain., Neguembor MV; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain., Castells-Garcia A; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China., Arganda-Carreras I; Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), Paseo Manuel Lardizabal 1, San Sebastian, Spain.; Donostia International Physics Center (DIPC), San Sebastian, Spain.; Ikerbasque, Basque Foundation for Science, Bilbao, Spain.; Biofisika Institute, Barrio Sarrena s/n, Leioa, Spain., Cosma MP; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.; ICREA, Barcelona, Spain.; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
Source: Nature machine intelligence [Nat Mach Intell] 2024; Vol. 6 (9), pp. 1021-1033. Date of Electronic Publication: 2024 Aug 27.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101740243 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2522-5839 (Electronic) Linking ISSN: 25225839 NLM ISO Abbreviation: Nat Mach Intell Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2522-5839
DOI:10.1038/s42256-024-00883-x