Title:	Predicting enzyme class from protein structural parameters and bagging predictors.
Authors:	YAMAGISHI, M. E. B. OLIVEIRA, S. R. M. BORRO, L. C. SANTOS, E. H. JARDINE, J. G. VIEIRA, F. D. MAZONI, I. NARCISO, M. G. KUSER-FALCÃO, P. R. NESHICH, G.
Affiliation:	MICHEL EDUARDO BELEZA YAMAGISHI, CNPTIA; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LUIZ C. BORRO; EDGARD HENRIQUE DOS SANTOS, CNPTIA; JOSÉ GILBERTO JARDINE, CNPTIA; FÁBIO DANILO VIEIRA, CNPTIA; IVAN MAZONI, CNPTIA; MARCELO GONCALVES NARCISO, CNPTIA; PAULA REGINA KUSER FALCÃO, CNPTIA; GORAN NESHICH, CNPTIA.
Date Issued:	2006
Citation:	In: ANNUAL INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS FOR MOLECULAR BIOLOGY, 14.; ANNUAL AB3C CONFERENCE, 2., 2006, Fortaleza. Conference Program... Fortaleza: ISCB, 2006.
Pages:	Não paginado.
Description:	Short Abstract: In this work we present a new method to classify enzymes that uses the STING_DB physical-chemical parameters and Bagging predictors. By building models based on "decision tree" and "neural network", we obtained an accuracy of 74% on average. These results outperform the similar models proposed in literature.
Thesagro:	Proteina Enzima
NAL Thesaurus:	Proteins Enzymes Bioinformatics
Keywords:	Parâmetros estruturais da proteína Parâmetros Bioinformática Sting_DB
Notes:	ISMB, X-MEETING 2006. Poster I-13.
Type of Material:	Resumo em anais e proceedings
Access:	openAccess
Appears in Collections:	Resumo em anais de congresso (CNPTIA)