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Positive-unlabeled learning for the prediction of conformational B-cell epitopes
BACKGROUND: The incomplete ground truth of training data of B-cell epitopes is a demanding issue in computational epitope prediction. The challenge is that only a small fraction of the surface residues of an antigen are confirmed as antigenic residues (positive training data); the remaining residues...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2015
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682424/ https://www.ncbi.nlm.nih.gov/pubmed/26681157 http://dx.doi.org/10.1186/1471-2105-16-S18-S12 |