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Reliable prediction of T-cell epitopes using neural networks with novel sequence representations
In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel input representation has been developed consisting of a combination of sparse encoding, Blosum encoding, and input derived from hidden Markov models. We demonstrate that the combination of several...
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| Main Authors: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Cold Spring Harbor Laboratory Press
2003
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2323871/ https://ncbi.nlm.nih.gov/pubmed/12717023 |
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