Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/106526
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.
Editor: 
Rights: fechado
Identifier DOI: 10.1007/978-3-540-85557-6_16
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-51849160890&partnerID=40&md5=90f2c6e587295073608d842778255850
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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