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Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations
BACKGROUND: Recently, information derived by correlated mutations in proteins has regained relevance for predicting protein contacts. This is due to new forms of mutual information analysis that have been proven to be more suitable to highlight direct coupling between pairs of residues in protein st...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2013
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3548674/ https://ncbi.nlm.nih.gov/pubmed/23368835 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-S1-S10 |
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