Using multivariate methods to infer knowledge from genomic data

Liliana López-Kleine, Nicolás Molano, Luis Ospina

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalInglés estadounidense
Páginas (desde-hasta)285-300
Número de páginas16
PublicaciónInternational Journal of Bioinformatics Research and Applications
Volumen9
N.º3
DOI
EstadoPublicada - ene 1 2013
Publicado de forma externa

All Science Journal Classification (ASJC) codes

  • Ingeniería biomédica
  • Informática aplicada a la salud
  • Bioquímica clínica
  • Gestión de información sanitaria

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