Knowledge-based generalization of metabolic networks: a practical study
ZHUKOVA, Anna
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
SHERMAN, David James
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
ZHUKOVA, Anna
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
SHERMAN, David James
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
< Leer menos
Models and Algorithms for the Genome [ MAGNOME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Idioma
en
Article de revue
Este ítem está publicado en
Journal of Bioinformatics and Computational Biology. 2014, vol. 12(2), n° 1441001
World Scientific Publishing
Resumen en inglés
The complex process of genome-scale metabolic network reconstruction involves semi- automatic reaction inference, analysis, and refinement through curation by human experts. Unfortunately, decisions by experts are hampered ...Leer más >
The complex process of genome-scale metabolic network reconstruction involves semi- automatic reaction inference, analysis, and refinement through curation by human experts. Unfortunately, decisions by experts are hampered by the complexity of the network, which can mask errors in the inferred network. In order to aid an expert in making sense out of the thousands of reactions in the organism's metabolism, we developed a method for knowledge-based generalization that provides a higher-level view of the network, highlighting the particularities and essential structure, while hiding the details. In this study, we show the application of this generalization method to 1286 metabolic networks of organisms in Path2Models that describe fatty acid metabolism. We compare the generalized networks and show that we successfully highlight the aspects that are important for their curation and comparison.< Leer menos
Palabras clave en inglés
Metabolic modeling
generalization
genome-scale reconstruction
fatty acid metabolism
Orígen
Importado de HalCentros de investigación