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	Provedor de dados Agronomy (1) Genet. Mol. Biol. (1) Horticultura Brasileira (1) Autor Baba,Viviane Yumi (1) Bento,Cintia dos S (1) Capel, Livia Santos (1) Carvalho,Francisco de A. T. de (1) Costa, Marcia Oliveira (1) Costa,Ivan G. (1) Gomes,Gisely Paula (1) Gonçalves,Leandro SA (1) Machado, Maria de Fátima Pires da Silva (1) Maldonado, Carlos (1) Mangolin, Claudete Aparecida (1) Mora, Freddy (1) Rodrigues,Rosana (1) Santos,Odair P dos (1) Souto,Marcílio C. P. de (1) Sudré,Cláudia P (1) Mais... Palavra-chave Clustering methods (3) Capsicum spp. (1) Cluster validation (1) Gene expression time series (1) Genetic diversity (1) Multivariate analysis (1) Qualitative and quantitative descriptors (1) RAPD-SSR loci (1) Self-organizing map algorithm. Genética Molecular (1) Unsupervised cross-validation (1) Mais... Tipo do documento Info:eu-repo/semantics/article (3) Ano 2019 (2) 2004 (1) País Brazil (3) Idioma Inglês (3)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 3 Primeira ... 1 ... Última Comparative analysis of clustering methods for gene expression time course data Genet. Mol. Biol. Costa,Ivan G.; Carvalho,Francisco de A. T. de; Souto,Marcílio C. P. de. This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series). Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification. Tipo: Info:eu-repo/semantics/article Palavras-chave: Clustering methods; Gene expression time series; Unsupervised cross-validation; Cluster validation. Ano: 2004 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400025 Combinations of distance measures and clustering algorithms in pepper germplasm characterization Horticultura Brasileira Gomes,Gisely Paula; Baba,Viviane Yumi; Santos,Odair P dos; Sudré,Cláudia P; Bento,Cintia dos S; Rodrigues,Rosana; Gonçalves,Leandro SA. ABSTRACT Characterization and evaluation of genotypes conserved in the germplasm banks have become of great importance due to gradual loss of genetic variability and search for more adapted and productive genotypes. This can be obtained through several ways, generating quantitative and qualitative data. Joint analysis of those variables may be considered a strategy for an accurate germplasm characterization. In this study we aimed to evaluate different clustering techniques for characterization and evaluation of Capsicum spp. accessions using combinations of specific measures for quantitative and qualitative variables. A collection of 56 Capsicum spp. accessions was characterized based on 25 morphoagronomic descriptors. Six quantitative distances were used... Tipo: Info:eu-repo/semantics/article Palavras-chave: Capsicum spp.; Multivariate analysis; Clustering methods; Genetic diversity; Qualitative and quantitative descriptors. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-05362019000200172 High genetic differentiation of grapevine rootstock varieties determined by molecular markers and artificial neural networks Agronomy Costa, Marcia Oliveira; Capel, Livia Santos; Maldonado, Carlos; Mora, Freddy; Mangolin, Claudete Aparecida; Machado, Maria de Fátima Pires da Silva. The genetic differentiation of grapevine rootstock varieties was inferred by the Artificial Neural Network approach based on the Self-Organizing Map algorithm. A combination of RAPD and SSR molecular markers, yielding polymorphic informative loci, was used to determine the genetic characterization among the rootstock varieties 420-A, Schwarzmann, IAC-766 Campinas, Traviú, Kober 5BB, and IAC-572 Jales. A neural network algorithm, based on allelic frequency, showed that the individual grapevine rootstocks (n = 64) were grouped into three genetically differentiated clusters. Cluster 1 included only the Kober 5BB rootstock, Cluster 2 included rootstocks of the varieties Traviú and IAC-572, and Cluster 3 included 420-A, Schwarzmann and IAC-766 plants. Evidence... Tipo: Info:eu-repo/semantics/article Palavras-chave: Clustering methods; RAPD-SSR loci; Self-organizing map algorithm. Genética Molecular. Ano: 2019 URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/43475 Registros recuperados: 3 Primeira ... 1 ... Última

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