Your browser doesn't support javascript.
loading
Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.
Quintero, Andrés; Ramírez, Jorge; Leal, Luis Guillermo; López-Kleine, Liliana.
Afiliação
  • Quintero A; Universidad Nacional de Colombia, Department of Biology, Master Student, Universidad Nacional de Colombia-Sede Bogotá
  • Ramírez J; Universidad Nacional de Colombia, School of Mathematics, Associate Professor, Universidad Nacional de Colombia-Sede Medellín.
  • Leal LG; Universidad Nacional de Colombia, Department of Statistics, Master Student, Universidad Nacional de Colombia-Sede Bogotá
  • López-Kleine L; Universidad Nacional de Colombia, Department of Statistics, Associate Professor, Universidad Nacional de Colombia-Sede Bogotá, Colombia.
Curr Genomics ; 15(5): 400-7, 2014 Oct.
Article em En | MEDLINE | ID: mdl-25435802
Relationships between genes are best represented using networks constructed from information of different types, with metabolic information being the most valuable and widely used for genetic network reconstruction. Other types of information are usually also available, and it would be desirable to systematically include them in algorithms for network reconstruction. Here, we present an algorithm to construct a global metabolic network that uses all available enzymatic and metabolic information about the organism. We construct a global enzymatic network (GEN) with a total of 4226 nodes (EC numbers) and 42723 edges representing all known metabolic reactions. As an example we use microarray data for Arabidopsis thaliana and combine it with the metabolic network constructing a final gene interaction network for this organism with 8212 nodes (genes) and 4606,901 edges. All scripts are available to be used for any organism for which genomic data is available.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article