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Type: Artigo de evento
Title: Prediction Of Protein-protein Binding Hot Spots: A Combination Of Classifiers Approach
Author: Higa R.H.
Tozzi C.L.
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. [4] for the same data set, when compared through a t-test with a significance level of 5%. © 2008 Springer-Verlag Berlin Heidelberg.
Rights: fechado
Identifier DOI: 10.1007/978-3-540-85557-6_16
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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