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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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Bibliographic Details
Main Authors: Savojardo, Castrense, Fariselli, Piero, Martelli, Pier Luigi, Casadio, Rita
Format: Artigo
Language:Inglês
Published: BioMed Central 2013
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Online Access: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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