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Accurate single-sequence prediction of solvent accessible surface area using local and global features
We present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window infor...
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| Publicado no: | Proteins |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4307928/ https://ncbi.nlm.nih.gov/pubmed/25204636 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/prot.24682 |
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