MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors.
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| Title: | MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors. |
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| Authors: | Shi H; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, China., Lin Y; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, China., Liu D; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, China., Zou Q; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, Zhejiang, China.; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2026 Mar 11; Vol. 22 (3), pp. e1013397. Date of Electronic Publication: 2026 Mar 11 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1013397 |
