Embeddings from protein language models predict conservation and variant effects

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1432-1203

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Embeddings from protein language models predict conservation and variant effects ; day:30 ; month:12 ; year:2021 ; pages:1-19
Human genetics ; (30.12.2021), 1-19

Creator: Marquet, Céline
Heinzinger, Michael
Olenyi, Tobias
Dallago, Christian
Erckert, Kyra
Bernhofer, Michael
Nechaev, Dmitrii
Rost, Burkhard

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00439-021-02411-y

URN: urn:nbn:de:101:1-2022041919180748891397

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

Last update: 15.08.2025, 7:39 AM CEST

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Marquet, Céline
Heinzinger, Michael
Olenyi, Tobias
Dallago, Christian
Erckert, Kyra
Bernhofer, Michael
Nechaev, Dmitrii
Rost, Burkhard
SpringerLink (Online service)

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Embeddings from protein language models predict conservation and variant effects

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Other Objects (12)

Protein embeddings predict binding residues in disordered regions

Applying BERT Embeddings to Predict Legal Textual Entailment

TMbed: transmembrane proteins predicted through language model embeddings

Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns

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Author Correction: Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns

Language with vision: A study on grounded word and sentence embeddings

Ion channel classification through machine learning and protein language model embeddings

Improving protein succinylation sites prediction using embeddings from protein language model

Integrating node embeddings and biological annotations for genes to predict disease-gene associations

Metric embeddings : bilipschitz and coarse embeddings into Banach spaces

Harmonic coarse embeddings

Protein embeddings predict binding residues in disordered regions

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TMbed: transmembrane proteins predicted through language model embeddings

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Using bundle embeddings to predict daily cortisol levels in human subjects

Author Correction: Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns

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Metric embeddings : bilipschitz and coarse embeddings into Banach spaces

Harmonic coarse embeddings

Protein embeddings predict binding residues in disordered regions

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