S2DA-GO: enhancing protein function prediction via gradient-decoupled cross-attention and semantic priors.
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| Title: | S2DA-GO: enhancing protein function prediction via gradient-decoupled cross-attention and semantic priors. |
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| Authors: | Wang H; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China., Xiang F; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China., Zhang J; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China., Wu T; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China., Wang D; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China.; Engineering Research Center of Intelligent Computing for Complex Energy Systems, Ministry of Education, Baoding, China.; Hebei Key Laboratory of Knowledge Computing for Energy & Power, Baoding, China., Wang Q; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China.; Engineering Research Center of Intelligent Computing for Complex Energy Systems, Ministry of Education, Baoding, China.; Hebei Key Laboratory of Knowledge Computing for Energy & Power, Baoding, China., Lu B; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China.; Engineering Research Center of Intelligent Computing for Complex Energy Systems, Ministry of Education, Baoding, China.; Hebei Key Laboratory of Knowledge Computing for Energy & Power, Baoding, China., Fu F; Yanzhao Electric Power Laboratory, North China Electric Power University, Baoding, China.; Department of Computer, North China Electric Power University, Baoding, China.; Engineering Research Center of Intelligent Computing for Complex Energy Systems, Ministry of Education, Baoding, China.; Hebei Key Laboratory of Knowledge Computing for Energy & Power, Baoding, China. |
| Source: | Frontiers in genetics [Front Genet] 2026 Jul 09; Vol. 17, pp. 1880976. Date of Electronic Publication: 2026 Jul 09 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101560621 Publication Model: eCollection Cited Medium: Print ISSN: 1664-8021 (Print) Linking ISSN: 16648021 NLM ISO Abbreviation: Front Genet Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-8021 |
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| DOI: | 10.3389/fgene.2026.1880976 |
