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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40954301 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Spatial gene expression at single-cell resolution from histology using deep learning with GHIST. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Fu+X%22">Fu X</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Cao+Y%22">Cao Y</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Bian+B%22">Bian B</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Wang+C%22">Wang C</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Graham+D%22">Graham D</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Pathmanathan+N%22">Pathmanathan N</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Patrick+E%22">Patrick E</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Kim+J%22">Kim J</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Yang+JYH%22">Yang JYH</searchLink>; 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. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101215604%22">Nature methods</searchLink> [Nat Methods] 2025 Sep; Vol. 22 (9), pp. 1900-1910. <i>Date of Electronic Publication: </i>2025 Sep 15. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Pub%2E+Group%22">Nature Pub. Group </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101215604 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1548-7105 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2215487091%22">15487091 </searchLink><i>NLM ISO Abbreviation: </i>Nat Methods <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40954301 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41592-025-02795-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 1900 Titles: – TitleFull: Spatial gene expression at single-cell resolution from histology using deep learning with GHIST. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fu X – PersonEntity: Name: NameFull: Cao Y – PersonEntity: Name: NameFull: Bian B – PersonEntity: Name: NameFull: Wang C – PersonEntity: Name: NameFull: Graham D – PersonEntity: Name: NameFull: Pathmanathan N – PersonEntity: Name: NameFull: Patrick E – PersonEntity: Name: NameFull: Kim J – PersonEntity: Name: NameFull: Yang JYH IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: 2025 Sep Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1548-7105 Numbering: – Type: volume Value: 22 – Type: issue Value: 9 Titles: – TitleFull: Nature methods Type: main |
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