EAGP: an efficient generative augmentation framework for phage protein classification under severe class imbalance.
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| Title: | EAGP: an efficient generative augmentation framework for phage protein classification under severe class imbalance. |
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| Authors: | Li J; Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong 266100, China., Li H; Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong 266100, China., Wang Y; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China.; Institute of Digital Health, Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003, China., Zou Q; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China.; Institute of Digital Health, Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003, China., Zhu H; Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China. |
| Source: | Bioinformatics (Oxford, England) [Bioinformatics] 2026 Jun 01; Vol. 42 (6). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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