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Using multivariate methods to infer knowledge from genomic data

Acceso Cerrado
ID Minciencias: ART-0001371002-4
Ranking: ART-ART_B

Abstract:

Since the introduction of genome sequencing techniques several methods for genomic data preprocessing and analysis have been published and applied to answer different biological questions. Rarely, multivariate methods have been used to extract knowledge about protein roles. Two of the most informative types of data are gene expression data (microarrays) and phylogenetic profiles indicating presence of genes in other organisms and therefore providing information about their co-evolution. Here we show that these two types of data, analyzed by means of principal component analysis and non parametric discriminant analysis, provide useful information about protein function and their participation in virulence processes.

Tópico:

Genomics and Phylogenetic Studies

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Citations: 2
2

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Información de la Fuente:

SCImago Journal & Country Rank
FuenteInternational Journal of Bioinformatics Research and Applications
Cuartil año de publicaciónNo disponible
Volumen9
Issue3
Páginas285 - 285
pISSNNo disponible
ISSN1744-5493

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