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Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction

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Bibliographic Details
Published in:Bioinformatics Advances : Journal of the International Society for Computational Biology
Format: Online Article RSS Article
Published: 2025
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container_title Bioinformatics Advances : Journal of the International Society for Computational Biology
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:18833
institution FRELIP
journal_source_facet Bioinformatics Advances : Journal of the International Society for Computational Biology
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
Biology
Natural Sciences — Life Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Life Sciences
sub_discipline_facet Natural Sciences — Life Sciences
subject_display Biology
Natural Sciences — Life Sciences
Natural Sciences
Biology
Natural Sciences — Life Sciences
Natural Sciences
subject_facet Biology
Natural Sciences — Life Sciences
Natural Sciences
title Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_auth Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_full Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_fullStr Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_full_unstemmed Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_short Node2Vec-DGI-EL: a hierarchical graph representation learning model for ingredient–disease association prediction
title_sort node2vec-dgi-el: a hierarchical graph representation learning model for ingredient–disease association prediction
topic Biology
Natural Sciences — Life Sciences
Natural Sciences
url https://academic.oup.com/bioinformaticsadvances/article/doi/10.1093/bioadv/vbaf216/8376334?rss=1