Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados Biol. Res. (1) Genet. Mol. Biol. (1) Autor Carvalho,André C.P.L.F. de (1) ERCISLI,SEZAI (1) Faceli,Katti (1) OZER,HAKAN (1) OZTURK,ERDOGAN (1) POLAT,TASKIN (1) SENGUL,MEMNUNE (1) Silva Jr,Wilson A. (1) TOSUN,MURAT (1) Mais... Palavra-chave Sage (2) Gene expression (1) Gene selection (1) Machine learning (1) Salvia (1) Total phenolic content (1) Mais... Tipo do documento Info:eu-repo/semantics/article (1) Journal article (1) Ano 2009 (1) 2004 (1) País Brazil (1) Chile (1) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Antioxidant Properties and Total Phenolic Content of Eight Salvia Species from Turkey Biol. Res. TOSUN,MURAT; ERCISLI,SEZAI; SENGUL,MEMNUNE; OZER,HAKAN; POLAT,TASKIN; OZTURK,ERDOGAN. Methanolic extracts of eight Salvia species, namely S. aethiopis, S. candidissima, S. limbata, S. microstegia, S. nemorosa, S. pachystachys, S. verticillata, and S. virgata, sampled from Eastern Anatolia in Turkey, were screened for their possible antioxidant activities by two complementary test systems, namely DPPH free radical scavenging and b-carotene/linoleic acid. Total phenolic content of the extracts of Salvia species were performed Folin-Ciocalteu reagent and gallic acid used as standard. A wide variation has been observed among species in terms of antioxidant activity and total phenolic content. In both DPPH and b-carotene system, the most active plant was Salvia verticillata with a value of IC50=18.3 μg/ml and 75.8%, respectively. This... Tipo: Journal article Palavras-chave: Sage; Salvia; Total phenolic content. Ano: 2009 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602009000200005 Evaluation of gene selection metrics for tumor cell classification Genet. Mol. Biol. Faceli,Katti; Carvalho,André C.P.L.F. de; Silva Jr,Wilson A.. Gene expression profiles contain the expression level of thousands of genes. Depending on the issue under investigation, this large amount of data makes analysis impractical. Thus, it is important to select subsets of relevant genes to work with. This paper investigates different metrics for gene selection. The metrics are evaluated based on their ability in selecting genes whose expression profile provides information to distinguish between tumor and normal tissues. This evaluation is made by constructing classifiers using the genes selected by each metric and then comparing the performance of these classifiers. The performance of the classifiers is evaluated using the error rate in the classification of new tissues. As the dataset has few tissue samples,... Tipo: Info:eu-repo/semantics/article Palavras-chave: Gene selection; Machine learning; Gene expression; Sage. Ano: 2004 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400029 Registros recuperados: 2 Primeira ... 1 ... Última

Empresa Brasileira de Pesquisa Agropecuária - Embrapa Todos os direitos reservados, conforme Lei n° 9.610 Política de Privacidade Área restrita		Embrapa Parque Estação Biológica - PqEB s/n° Brasília, DF - Brasil - CEP 70770-901 Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco