MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning

Authors

Zhijian Huang (ORCID: https://orcid.org/0000-0003-1601-3802)
Ziyu Fan (ORCID: https://orcid.org/0009-0003-1962-8092)
Lei Deng (ORCID: https://orcid.org/0000-0003-2869-1619)
Min Wu (ORCID: https://orcid.org/0000-0003-0977-3600)
Siyuan Shen (ORCID: https://orcid.org/0009-0005-3752-2368)

Institutions

Agency for Science, Technology and Research (SG)
Central South University (CN)
Institute for Infocomm Research (SG)

Publication Details

Journal: Bioinformatics
Published: 2024-09-01
DOI: https://doi.org/10.1093/bioinformatics/btae386
Citations: 9
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 3.25

Funders

National Natural Science Foundation of China

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article

MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning

Zhijian Huang, Ziyu Fan, Lei Deng, Min Wu et al.

Sep 1, 2024

9 citations

Bioinformatics

Computational Drug Discovery Methods

3.25

article

MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning

Zhijian Huang, Ziyu Fan, Lei Deng, Min Wu, Siyuan Shen

September 1, 2024article en

9 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 40(Supplement_2)

Agency for Science, Technology and Research (SG), Central South University (CN), Institute for Infocomm Research (SG)

National Natural Science Foundation of China

Openalex Percentile: Top 7%

Computational Drug Discovery Methods

3.25

DOI Open Access PDF OpenAlex

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