Spatial gene expression at single-cell resolution from histology using deep learning with GHIST.
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| Title: | Spatial gene expression at single-cell resolution from histology using deep learning with GHIST. |
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| Authors: | Fu X; School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.; School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China., Cao Y; School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China., Bian B; School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia., Wang C; School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China., Graham D; Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia.; Westmead Breast Cancer Institute, Westmead Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia.; Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia., Pathmanathan N; Westmead Breast Cancer Institute, Westmead Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia.; Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.; Douglass Hanly Moir Pathology, Sydney, New South Wales, Australia., Patrick E; School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China.; Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia., Kim J; School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China., Yang JYH; School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia. jean.yang@sydney.edu.au.; Sydney Precision Data Science Centre, University of Sydney, Sydney, New South Wales, Australia. jean.yang@sydney.edu.au.; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia. jean.yang@sydney.edu.au.; Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, China. jean.yang@sydney.edu.au. |
| Source: | Nature methods [Nat Methods] 2025 Sep; Vol. 22 (9), pp. 1900-1910. Date of Electronic Publication: 2025 Sep 15. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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