View in EDS

Phenotypic prediction of missense variants via deep contrastive learning.

Saved in:
Bibliographic Details
Title: Phenotypic prediction of missense variants via deep contrastive learning.
Authors: Wen J; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA.; Biological and Life Sciences Division, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates., Zeng S; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA., Bonzel CL; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA., Kobren SN; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Du J; Department of Statistics, University of Chicago, Chicago, IL, USA., Chai Y; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore., Wang H; Department of Computer Science, Rutgers University, Piscataway, NJ, USA., Zhu M; Department of Genetics, Harvard Medical School, Boston, MA, USA., Chen S; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Human Genetics, The University of Chicago, Chicago, IL, USA., Leng F; Howard Hughes Medical Institute and Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA., Zhang HG; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA., Liao KP; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA., Cho K; VA Boston Healthcare System, Boston, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA., Kohane IS; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Zitnik M; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA.; Harvard Data Science Initiative, Cambridge, MA, USA., Pereira AC; Brigham and Women's Hospital, Boston, MA, USA., Liu JS; Department of Statistics and Data Science, Tsinghua University, Beijing, China.; Department of Statistics, Harvard University, Cambridge, MA, USA., Cai T; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. tcai@hsph.harvard.edu.; VA Boston Healthcare System, Boston, MA, USA. tcai@hsph.harvard.edu.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. tcai@hsph.harvard.edu.
Source: Nature biomedical engineering [Nat Biomed Eng] 2026 Apr 14. Date of Electronic Publication: 2026 Apr 14.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101696896 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2157-846X (Electronic) Linking ISSN: 2157846X NLM ISO Abbreviation: Nat Biomed Eng Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41981312
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Phenotypic prediction of missense variants via deep contrastive learning.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Wen+J%22">Wen J</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA.; Biological and Life Sciences Division, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates.<br /><searchLink fieldCode="AU" term="%22Zeng+S%22">Zeng S</searchLink>; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.<br /><searchLink fieldCode="AU" term="%22Bonzel+CL%22">Bonzel CL</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Kobren+SN%22">Kobren SN</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Du+J%22">Du J</searchLink>; Department of Statistics, University of Chicago, Chicago, IL, USA.<br /><searchLink fieldCode="AU" term="%22Chai+Y%22">Chai Y</searchLink>; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.<br /><searchLink fieldCode="AU" term="%22Wang+H%22">Wang H</searchLink>; Department of Computer Science, Rutgers University, Piscataway, NJ, USA.<br /><searchLink fieldCode="AU" term="%22Zhu+M%22">Zhu M</searchLink>; Department of Genetics, Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Chen+S%22">Chen S</searchLink>; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Human Genetics, The University of Chicago, Chicago, IL, USA.<br /><searchLink fieldCode="AU" term="%22Leng+F%22">Leng F</searchLink>; Howard Hughes Medical Institute and Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Zhang+HG%22">Zhang HG</searchLink>; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Liao+KP%22">Liao KP</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; VA Boston Healthcare System, Boston, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Cho+K%22">Cho K</searchLink>; VA Boston Healthcare System, Boston, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Kohane+IS%22">Kohane IS</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Zitnik+M%22">Zitnik M</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Boston, MA, USA.; Harvard Data Science Initiative, Cambridge, MA, USA.<br /><searchLink fieldCode="AU" term="%22Pereira+AC%22">Pereira AC</searchLink>; Brigham and Women's Hospital, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Liu+JS%22">Liu JS</searchLink>; Department of Statistics and Data Science, Tsinghua University, Beijing, China.; Department of Statistics, Harvard University, Cambridge, MA, USA.<br /><searchLink fieldCode="AU" term="%22Cai+T%22">Cai T</searchLink>; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. tcai@hsph.harvard.edu.; VA Boston Healthcare System, Boston, MA, USA. tcai@hsph.harvard.edu.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. tcai@hsph.harvard.edu.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101696896%22">Nature biomedical engineering</searchLink> [Nat Biomed Eng] 2026 Apr 14. <i>Date of Electronic Publication: </i>2026 Apr 14.
– 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="%22Springer+Nature%22">Springer Nature </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101696896 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2157-846X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222157846X%22">2157846X </searchLink><i>NLM ISO Abbreviation: </i>Nat Biomed Eng <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41981312
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/s41551-026-01636-4
    Languages:
      – Code: eng
        Text: English
    Titles:
      – TitleFull: Phenotypic prediction of missense variants via deep contrastive learning.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wen J
      – PersonEntity:
          Name:
            NameFull: Zeng S
      – PersonEntity:
          Name:
            NameFull: Bonzel CL
      – PersonEntity:
          Name:
            NameFull: Kobren SN
      – PersonEntity:
          Name:
            NameFull: Du J
      – PersonEntity:
          Name:
            NameFull: Chai Y
      – PersonEntity:
          Name:
            NameFull: Wang H
      – PersonEntity:
          Name:
            NameFull: Zhu M
      – PersonEntity:
          Name:
            NameFull: Chen S
      – PersonEntity:
          Name:
            NameFull: Leng F
      – PersonEntity:
          Name:
            NameFull: Zhang HG
      – PersonEntity:
          Name:
            NameFull: Liao KP
      – PersonEntity:
          Name:
            NameFull: Cho K
      – PersonEntity:
          Name:
            NameFull: Kohane IS
      – PersonEntity:
          Name:
            NameFull: Zitnik M
      – PersonEntity:
          Name:
            NameFull: Pereira AC
      – PersonEntity:
          Name:
            NameFull: Liu JS
      – PersonEntity:
          Name:
            NameFull: Cai T
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 14
              M: 04
              Text: 2026 Apr 14
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 2157-846X
          Titles:
            – TitleFull: Nature biomedical engineering
              Type: main
ResultId 1