F-MAP: A Bayesian approach to infer the gene regulatory network using external hints.
PLoS One
; 12(9): e0184795, 2017.
Article
en En
| MEDLINE
| ID: mdl-28938012
ABSTRACT
The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Perfilación de la Expresión Génica
/
Redes Reguladoras de Genes
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2017
Tipo del documento:
Article
País de afiliación:
Irán