An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes.
C R Biol
; 337(12): 661-78, 2014 Dec.
Article
en En
| MEDLINE
| ID: mdl-25433558
ABSTRACT
Target identification aims at identifying biomolecules whose function should be therapeutically altered to cure the considered pathology. An algorithm for in silico target identification using Boolean network attractors is proposed. It assumes that attractors correspond to phenotypes produced by the modeled biological network. It identifies target combinations which allow disturbed networks to avoid attractors associated with pathological phenotypes. The algorithm is tested on a Boolean model of the mammalian cell cycle and its applications are illustrated on a Boolean model of Fanconi anemia. Results show that the algorithm returns target combinations able to remove attractors associated with pathological phenotypes and then succeeds in performing the proposed in silico target identification. However, as with any in silico evidence, there is a bridge to cross between theory and practice. Nevertheless, it is expected that the algorithm is of interest for target identification.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Simulación por Computador
/
Redes Neurales de la Computación
/
Descubrimiento de Drogas
/
Ensayos Analíticos de Alto Rendimiento
Tipo de estudio:
Diagnostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
C R Biol
Asunto de la revista:
BIOLOGIA
Año:
2014
Tipo del documento:
Article