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A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.

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Title: A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.
Authors: Nguyen TT; Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Viet Nam., Zheng W; Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore., Nguyen VN; Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Viet Nam., Le NQK; In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan; AIBioMed Research Group, Taipei Medical University, Taipei, 110, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, 110, Taiwan. Electronic address: khanhlee@tmu.edu.tw., Chua MCH; Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. Electronic address: matthewchua@nus.edu.sg.
Source: Computational biology and chemistry [Comput Biol Chem] 2026 Feb; Vol. 120 (Pt 1), pp. 108609. Date of Electronic Publication: 2025 Aug 15.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 101157394 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-928X (Electronic) Linking ISSN: 14769271 NLM ISO Abbreviation: Comput Biol Chem Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.
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  Data: <searchLink fieldCode="AU" term="%22Nguyen+TT%22">Nguyen TT</searchLink>; Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Viet Nam.<br /><searchLink fieldCode="AU" term="%22Zheng+W%22">Zheng W</searchLink>; Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.<br /><searchLink fieldCode="AU" term="%22Nguyen+VN%22">Nguyen VN</searchLink>; Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Viet Nam.<br /><searchLink fieldCode="AU" term="%22Le+NQK%22">Le NQK</searchLink>; In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan; AIBioMed Research Group, Taipei Medical University, Taipei, 110, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, 110, Taiwan. Electronic address: khanhlee@tmu.edu.tw.<br /><searchLink fieldCode="AU" term="%22Chua+MCH%22">Chua MCH</searchLink>; Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. Electronic address: matthewchua@nus.edu.sg.
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  Data: <searchLink fieldCode="JN" term="%22101157394%22">Computational biology and chemistry</searchLink> [Comput Biol Chem] 2026 Feb; Vol. 120 (Pt 1), pp. 108609. <i>Date of Electronic Publication: </i>2025 Aug 15.
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  Data: Journal Article; Research Support, Non-U.S. Gov't
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101157394 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1476-928X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214769271%22">14769271 </searchLink><i>NLM ISO Abbreviation: </i>Comput Biol Chem <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.compbiolchem.2025.108609
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      – Code: eng
        Text: English
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        StartPage: 108609
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      – TitleFull: A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.
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              Text: 2026 Feb
              Type: published
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