Protein function prediction as approximate semantic entailment

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Protein function prediction as approximate semantic entailment ; volume:6 ; number:2 ; day:14 ; month:2 ; year:2024 ; pages:220-228 ; date:2.2024
Nature machine intelligence ; 6, Heft 2 (14.2.2024), 220-228, 2.2024

Classification: Ingenieurwissenschaften und Maschinenbau

Creator: Kulmanov, Maxat
Guzmán-Vega, Francisco J.
Duek Roggli, Paula
Lane, Lydie
Arold, Stefan T.
Hoehndorf, Robert

Contributor: SpringerLink (Online service)

DOI: 10.1038/s42256-024-00795-w

URN: urn:nbn:de:101:1-2404291021337.141752556590

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:45 AM CEST

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Kulmanov, Maxat
Guzmán-Vega, Francisco J.
Duek Roggli, Paula
Lane, Lydie
Arold, Stefan T.
Hoehndorf, Robert
SpringerLink (Online service)

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Protein function prediction as approximate semantic entailment

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Other Objects (12)

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Integrating multiple networks for protein function prediction

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Deep learning methods for protein function prediction

An iterative approach of protein function prediction

Prediction of Protein Function through Machine Learning

Interspecies gene function prediction using semantic similarity

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Protein function prediction using domain families

Approximate Bayesian neural networks in genomic prediction

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Consistent probabilistic outputs for protein function prediction

Integrating multiple networks for protein function prediction

NPF:network propagation for protein function prediction

Deep learning methods for protein function prediction

An iterative approach of protein function prediction

Prediction of Protein Function through Machine Learning

Interspecies gene function prediction using semantic similarity

Improved multi-level protein–protein interaction prediction with semantic-based regularization

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