View in EDS

Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.

Saved in:
Bibliographic Details
Title: Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.
Authors: Gunawan I; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.; School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia., Kohane FV; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia., Dey M; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia., Nguyen K; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia., Zheng Y; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.; Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia., Neumann DP; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia., Vafaee F; School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, NSW, Australia.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia., Meijering E; School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia., Lock JG; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.; Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia. john.lock@unsw.edu.au.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.
Source: Nature communications [Nat Commun] 2025 May 17; Vol. 16 (1), pp. 4606. Date of Electronic Publication: 2025 May 17.
Publication Type: Journal Article
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
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 40382312
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Gunawan+I%22">Gunawan I</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.; School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Kohane+FV%22">Kohane FV</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Dey+M%22">Dey M</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Nguyen+K%22">Nguyen K</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Zheng+Y%22">Zheng Y</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.; Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Neumann+DP%22">Neumann DP</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Vafaee+F%22">Vafaee F</searchLink>; School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, NSW, Australia.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Meijering+E%22">Meijering E</searchLink>; School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia.<br /><searchLink fieldCode="AU" term="%22Lock+JG%22">Lock JG</searchLink>; School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.; Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia. john.lock@unsw.edu.au.; UNSW Data Science Hub, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.; UNSW Artificial Intelligence Institute, University of New South Wales, Sydney, NSW, Australia. john.lock@unsw.edu.au.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101528555%22">Nature communications</searchLink> [Nat Commun] 2025 May 17; Vol. 16 (1), pp. 4606. <i>Date of Electronic Publication: </i>2025 May 17.
– 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>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
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40382312
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/s41467-025-59592-7
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 4606
    Titles:
      – TitleFull: Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Gunawan I
      – PersonEntity:
          Name:
            NameFull: Kohane FV
      – PersonEntity:
          Name:
            NameFull: Dey M
      – PersonEntity:
          Name:
            NameFull: Nguyen K
      – PersonEntity:
          Name:
            NameFull: Zheng Y
      – PersonEntity:
          Name:
            NameFull: Neumann DP
      – PersonEntity:
          Name:
            NameFull: Vafaee F
      – PersonEntity:
          Name:
            NameFull: Meijering E
      – PersonEntity:
          Name:
            NameFull: Lock JG
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 17
              M: 05
              Text: 2025 May 17
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-electronic
              Value: 2041-1723
          Numbering:
            – Type: volume
              Value: 16
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Nature communications
              Type: main
ResultId 1