Anti-symmetric framework for balanced learning of protein–protein interactions

Authors

Weizhuo Li (ORCID: https://orcid.org/0000-0002-2298-2901)
Yuansheng Liu (ORCID: https://orcid.org/0000-0002-7680-3155)
Xiangxiang Zeng (ORCID: https://orcid.org/0000-0001-6201-0114)
Tao Tang (ORCID: https://orcid.org/0000-0002-1207-4192)
Tianyang Li (ORCID: https://orcid.org/0000-0002-6005-0734)
Xiaofeng Cao

Institutions

Hunan University (CN)
Jilin University (CN)
Changsha University (CN)
Nanjing University of Posts and Telecommunications (CN)
Changchun University (CN)

Publication Details

Journal: Bioinformatics
Published: 2024-10-01
DOI: https://doi.org/10.1093/bioinformatics/btae603
Citations: 15
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 5.42

Funders

National Natural Science Foundation of China

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article

Anti-symmetric framework for balanced learning of protein–protein interactions

Weizhuo Li, Yuansheng Liu, Xiangxiang Zeng, Tao Tang et al.

Oct 1, 2024

15 citations

Bioinformatics

Computational Drug Discovery Methods

5.42

article

Anti-symmetric framework for balanced learning of protein–protein interactions

Weizhuo Li, Yuansheng Liu, Xiangxiang Zeng, Tao Tang, Tianyang Li, Xiaofeng Cao

October 1, 2024article en

15 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 40(10)

Hunan University (CN), Jilin University (CN), Changsha University (CN), Nanjing University of Posts and Telecommunications (CN), Changchun University (CN)

National Natural Science Foundation of China

Openalex Percentile: Top 4%

Computational Drug Discovery Methods

5.42

DOI Open Access PDF OpenAlex

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