GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure
GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been primarily used for these prediction models, it is difficult to interpret the models reported thus far as...
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Full title
GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure
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TN_cdi_doaj_primary_oai_doaj_org_article_0e2e7373bec94ec09aa483e8a23c2e92
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0e2e7373bec94ec09aa483e8a23c2e92
Other Identifiers
ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0291223
