Weighted-LASSO for structured network inference from time course data.
Stat Appl Genet Mol Biol
; 9: Article 15, 2010.
Article
en En
| MEDLINE
| ID: mdl-20196750
ABSTRACT
We present a weighted-LASSO method to infer the parameters of a first-order vector auto-regressive model that describes time course expression data generated by directed gene-to-gene regulation networks. These networks are assumed to own prior internal structures of connectivity which drive the inference method. This prior structure can be either derived from prior biological knowledge or inferred by the method itself. We illustrate the performance of this structure-based penalization both on synthetic data and on two canonical regulatory networks (the yeast cell cycle regulation network and the E. coli S.O.S. DNA repair network).
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Análisis de Regresión
/
Análisis de Secuencia por Matrices de Oligonucleótidos
/
Perfilación de la Expresión Génica
/
Redes Reguladoras de Genes
Tipo de estudio:
Diagnostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Stat Appl Genet Mol Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA
Año:
2010
Tipo del documento:
Article