High-throughput electronic biology: mining information for drug discovery.
Nat Rev Drug Discov
; 6(3): 220-30, 2007 Mar.
Article
en En
| MEDLINE
| ID: mdl-17330071
The vast range of in silico resources that are available in life sciences research hold much promise towards aiding the drug discovery process. To fully realize this opportunity, computational scientists must consider the practical issues of data integration and identify how best to apply these resources scientifically. In this article we describe in silico approaches that are driven towards the identification of testable laboratory hypotheses; we also address common challenges in the field. We focus on flexible, high-throughput techniques, which may be initiated independently of 'wet-lab' experimentation, and which may be applied to multiple disease areas. The utility of these approaches in drug discovery highlights the contribution that in silico techniques can make and emphasizes the need for collaboration between the areas of disease research and computational science.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Diseño de Fármacos
/
Almacenamiento y Recuperación de la Información
/
Internet
/
Biología de Sistemas
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Nat Rev Drug Discov
Asunto de la revista:
FARMACOLOGIA
/
TERAPIA POR MEDICAMENTOS
Año:
2007
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Reino Unido