Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
About this item
Full title
Author / Creator
Lee, Taeheon , Lee, Sangseon , Kang, Minji and Kim, Sun
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
GPCR proteins belong to diverse families of proteins that are defined at multiple hierarchical levels. Inspecting relationships between GPCR proteins on the hierarchical structure is important, since characteristics of the protein can be inferred from proteins in similar hierarchical information. However, modeling of GPCR families has been performe...
Alternative Titles
Full title
Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_84143de8168042d6864cb0ea665b6216
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_84143de8168042d6864cb0ea665b6216
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-021-88623-8
