L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2105

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions ; volume:20 ; number:8 ; day:10 ; month:6 ; year:2019 ; pages:1-13 ; date:6.2019
BMC bioinformatics ; 20, Heft 8 (10.6.2019), 1-13, 6.2019

Classification: Biowissenschaften, Biologie

Creator: Cui, Zhen
Gao, Ying-Lian
Liu, Jin-Xing
Dai, Ling-Yun
Yuan, Sha-Sha

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12859-019-2768-7

URN: urn:nbn:de:101:1-2019110419181652906798

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

Last update: 15.08.2025, 7:26 AM CEST

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Cui, Zhen
Gao, Ying-Lian
Liu, Jin-Xing
Dai, Ling-Yun
Yuan, Sha-Sha
SpringerLink (Online service)

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L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions

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Other Objects (12)

Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction

Graph regularized non-negative matrix factorization with $$L_2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Regularized online tensor factorization for sparse knowledge graph embeddings

Double regularized matrix factorization for image classification and clustering

Motor data-regularized nonnegative matrix factorization for ego-noise suppression

DASPfind: new efficient method to predict drug–target interactions

Co-regularized multiview nonnegative matrix factorization with correlation constraint for representation learning

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Graph regularized L 2,1-nonnegative matrix factorization for miRNA-disease association prediction

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Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction

Graph regularized non-negative matrix factorization with $$L_2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction

Regularized online tensor factorization for sparse knowledge graph embeddings

Double regularized matrix factorization for image classification and clustering

Motor data-regularized nonnegative matrix factorization for ego-noise suppression

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Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction

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Regularized online tensor factorization for sparse knowledge graph embeddings

Double regularized matrix factorization for image classification and clustering

Motor data-regularized nonnegative matrix factorization for ego-noise suppression

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Co-regularized multiview nonnegative matrix factorization with correlation constraint for representation learning

A unified solution for different scenarios of predicting drug-target interactions via triple matrix factorization

Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization

Graph regularized L 2,1-nonnegative matrix factorization for miRNA-disease association prediction

Protein functional properties prediction in sparsely-label PPI networks through regularized non-negative matrix factorization

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