The prediction results of B-cell epitope in F. hepatica using deep learning and machine learning models.

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Bibliographic Details
Main Author:	Rui-Si Hu (5337227) (author)
Other Authors:	Kui Gu (12335571) (author), Muhammad Ehsan (2561170) (author), Sayed Haidar Abbas Raza (8452353) (author), Chun-Ren Wang (128559) (author)
Published:	2025
Subjects:	Biochemistry Microbiology Biotechnology Immunology Infectious Diseases Virology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified therapeutic antibody development superior predictive power seven synthetic peptides offer efficient solutions fasciola hepatica </ blot immunoassays confirmed 12 handcrafted features predict linear bces enhance prediction accuracy cell epitope prediction based vaccine design xlink "> deepbce xlink "> cell epitopes based vaccines valuable tool structural complexity specific binding proteomic data present deepbce positive sera peptide sequences parasitic pathogens machine learning leucine aminopeptidase independent testing igg reactivity high cost fold cross diagnostic applications deep learning concept study comparative analyses case study attention mechanism artificial intelligence art self approximately 81
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The prediction results of B-cell epitope in <i>F. hepatica</i> using deep learning and machine learning models.