English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/1425
Compartir / Impacto:
Estadísticas
Add this article to your Mendeley library MendeleyBASE
Citado 11 veces en Web of Knowledge®  |  Pub MebCentral Ver citas en PubMed Central  |  Ver citas en Google académico
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar otros formatos: Exportar EndNote (RIS)Exportar EndNote (RIS)Exportar EndNote (RIS)
Título : A literature-based similarity metric for biological processes
Autor : Chagoyen, Mónica; Carmona-Sáez, Pedro; Gil, Concha; Carazo, José M.; Pascual-Montano, Alberto
Fecha de publicación : 26-jul-2006
Editor: BioMed Central
Citación : BMC Bioinformatics 2006, 7:363
Resumen: [Background] Recent analyses in systems biology pursue the discovery of functional modules within the cell. Recognition of such modules requires the integrative analysis of genome-wide experimental data together with available functional schemes. In this line, methods to bridge the gap between the abstract definitions of cellular processes in current schemes and the interlinked nature of biological networks are required.
[Results] This work explores the use of the scientific literature to establish potential relationships among cellular processes. To this purpose we have used a document based similarity method to compute pair-wise similarities of the biological processes described in the Gene Ontology (GO). The method has been applied to the biological processes annotated for the Saccharomyces cerevisiae genome. We compared our results with similarities obtained with two ontology-based metrics, as well as with gene product annotation relationships. We show that the literature-based metric conserves most direct ontological relationships, while reveals biologically sounded similarities that are not obtained using ontology-based metrics and/or genome annotation.
[Conclusion] The scientific literature is a valuable source of information from which to compute similarities among biological processes. The associations discovered by literature analysis are a valuable complement to those encoded in existing functional schemes, and those that arise by genome annotation. These similarities can be used to conveniently map the interlinked structure of cellular processes in a particular organism.
URI : http://hdl.handle.net/10261/1425
DOI: 10.1186/1471-2105-7-363
ISSN: 1471-2105
Aparece en las colecciones: (CNB) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
1471-2105-7-363.pdf366,02 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 



NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.