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|Type:||Artigo de evento|
|Title:||Prediction Of Protein-protein Binding Hot Spots: A Combination Of Classifiers Approach|
|Abstract:||In this work we approach the problem of predicting protein binding hot spot residues through a combination of classifiers. We consider a comprehensive set of structural and chemical properties reported in the literature for characterizing hot spot residues. Each component classifier considers a specific set of properties as feature set and their output are combined by the mean rule. The proposed combination of classifiers achieved a performance of 56.6%, measured by the F-Measure with corresponding Recall of 72.2% and Precision of 46.6%. This performance is higher than those reported by Darnel et al.  for the same data set, when compared through a t-test with a significance level of 5%. © 2008 Springer-Verlag Berlin Heidelberg.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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