English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/153395
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Factors affecting interactome-based prediction of human genes associated with clinical signs

AutorGonzález-Pérez, Sara; Pazos, Florencio; Chagoyen, Mónica
Palabras claveGene prioritization
Human interactome
Clinical signs
Network-based methods
Fecha de publicación17-jul-2017
EditorBioMed Central
CitaciónBMC Bioinformatics 18(1): 340 (2017)
Resumen[Background] Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome.
[Results] Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes involved (mono- vs. oligogenic diseases), mode of inheritance, type of clinical sign and gene product function.
[Conclusions] Our results indicate that the characteristics of the clinical signs and their related diseases should be considered for interpreting the results of network-prediction methods, such as those aimed at discovering disease-related genes and variants. These results are important due the increasing use of clinical signs as an alternative to diseases for studying the molecular basis of human pathologies.
Versión del editorhttp://dx.doi.org/10.1186/s12859-017-1754-1
Aparece en las colecciones: (CNB) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
12859_2017_Article_1754.pdf1,26 MBAdobe PDFVista previa
Mostrar el registro completo

Artículos relacionados:

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