Quantitative network measures as biomarkers for classifying prostate cancer disease states: a systems approach to diagnostic biomarkers.
PLoS One
; 8(11): e77602, 2013.
Article
en En
| MEDLINE
| ID: mdl-24236006
ABSTRACT
Identifying diagnostic biomarkers based on genomic features for an accurate disease classification is a problem of great importance for both, basic medical research and clinical practice. In this paper, we introduce quantitative network measures as structural biomarkers and investigate their ability for classifying disease states inferred from gene expression data from prostate cancer. We demonstrate the utility of our approach by using eigenvalue and entropy-based graph invariants and compare the results with a conventional biomarker analysis of the underlying gene expression data.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Próstata
/
Biomarcadores de Tumor
/
Perfilación de la Expresión Génica
/
Modelos Biológicos
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Aspecto:
Patient_preference
Límite:
Humans
/
Male
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2013
Tipo del documento:
Article
País de afiliación:
Austria