Author Correction: scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses.
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| Title: | Author Correction: scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. |
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| Authors: | Wang J; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA., Ma A; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA., Chang Y; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA., Gong J; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA., Jiang Y; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA., Qi R; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA., Wang C; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA., Fu H; Department of Neuroscience, The Ohio State University, Columbus, OH, USA., Ma Q; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA. qin.ma@osumc.edu., Xu D; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA. xudong@missouri.edu. |
| Source: | Nature communications [Nat Commun] 2022 May 04; Vol. 13 (1), pp. 2554. Date of Electronic Publication: 2022 May 04. |
| Publication Type: | Published Erratum |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 35508488 AccessLevel: 2 PubTypeId: unknown PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Author Correction: scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Wang+J%22">Wang J</searchLink>; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.<br /><searchLink fieldCode="AU" term="%22Ma+A%22">Ma A</searchLink>; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.<br /><searchLink fieldCode="AU" term="%22Chang+Y%22">Chang Y</searchLink>; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.<br /><searchLink fieldCode="AU" term="%22Gong+J%22">Gong J</searchLink>; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.<br /><searchLink fieldCode="AU" term="%22Jiang+Y%22">Jiang Y</searchLink>; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.<br /><searchLink fieldCode="AU" term="%22Qi+R%22">Qi R</searchLink>; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.<br /><searchLink fieldCode="AU" term="%22Wang+C%22">Wang C</searchLink>; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.<br /><searchLink fieldCode="AU" term="%22Fu+H%22">Fu H</searchLink>; Department of Neuroscience, The Ohio State University, Columbus, OH, USA.<br /><searchLink fieldCode="AU" term="%22Ma+Q%22">Ma Q</searchLink>; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA. qin.ma@osumc.edu.<br /><searchLink fieldCode="AU" term="%22Xu+D%22">Xu D</searchLink>; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA. xudong@missouri.edu. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101528555%22">Nature communications</searchLink> [Nat Commun] 2022 May 04; Vol. 13 (1), pp. 2554. <i>Date of Electronic Publication: </i>2022 May 04. – Name: TypePub Label: Publication Type Group: TypPub Data: Published Erratum – 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>England <i>NLM ID: </i>101528555 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2041-1723 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220411723%22">20411723 </searchLink><i>NLM ISO Abbreviation: </i>Nat Commun <i>Subsets: </i>MEDLINE; PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=35508488 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41467-022-30331-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 2554 Titles: – TitleFull: Author Correction: scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang J – PersonEntity: Name: NameFull: Ma A – PersonEntity: Name: NameFull: Chang Y – PersonEntity: Name: NameFull: Gong J – PersonEntity: Name: NameFull: Jiang Y – PersonEntity: Name: NameFull: Qi R – PersonEntity: Name: NameFull: Wang C – PersonEntity: Name: NameFull: Fu H – PersonEntity: Name: NameFull: Ma Q – PersonEntity: Name: NameFull: Xu D IsPartOfRelationships: – BibEntity: Dates: – D: 04 M: 05 Text: 2022 May 04 Type: published Y: 2022 Identifiers: – Type: issn-electronic Value: 2041-1723 Numbering: – Type: volume Value: 13 – Type: issue Value: 1 Titles: – TitleFull: Nature communications Type: main |
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