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Prediction of the disulfide-bonding state of cysteines in proteins at 88% accuracy
The task of predicting the cysteine-bonding state in proteins starting from the residue chain is addressed by implementing a new hybrid system that combines a neural network and a hidden Markov model (hidden neural network). Training is performed using 4136 cysteine-containing segments extracted fro...
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| Auteurs principaux: | , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Cold Spring Harbor Laboratory Press
2002
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2373728/ https://ncbi.nlm.nih.gov/pubmed/12381855 |
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