Data/hora: 06/06/2024 03:37:23

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	07/01/2010	
Data da última atualização: 	15/01/2020	
Autoria: 	HIGA, R. H.; TOZZI, C. L.	
Afiliação: 	ROBERTO HIROSHI HIGA, CNPTIA; CLÉSIO LUIS TOZZI, FEEC/Unicamp.	
Título: 	Prediction of protein-protein binding hot spots: a combination of classifiers approach.	
Ano de publicação: 	2008	
Fonte/Imprenta: 	In: BRAZILIAN SYMPOSIUM ON BIOINFORMATICS, 3., 2008, Santo André, SP. Advances in bioinformatics and computational biology: proceedings. Berlin: Springer, 2008.	
Páginas: 	p. 165-168.	
Série: 	(Lecture notes in bioinformatics, 5167).	
DOI: 	10.1007/978-3-540-85557-6_16	
Idioma: 	Inglês	
Notas: 	BSB 2008.	
Conteúdo: 	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%.	
Palavras-Chave: 	Combination of classifiers; Hot spots; Interações proteína-proteína; Propriedades estruturais de proteínas; Propriedades químicas de proteínas.	
Thesaurus Nal: 	Binding sites; Protein-protein interactions.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (14424-1) - UPC - AA - PP -  -  - 2010.00003 - DES
CNPTIA - (14424-2) - UPC - AA - DD -  -  -  - DIS