Detecting survival-associated biomarkers from heterogeneous populations.

Saegusa, Takumi; Zhao, Zhiwei; Ke, Hongjie; Ye, Zhenyao; Xu, Zhongying; Chen, Shuo; Ma, Tianzhou

Saegusa, Takumi; Zhao, Zhiwei; Ke, Hongjie; Ye, Zhenyao; Xu, Zhongying; Chen, Shuo; Ma, Tianzhou.

Afiliación

Saegusa T; Department of Mathematics, University of Maryland, College Park, MD, 20742, USA.
Zhao Z; Department of Mathematics, University of Maryland, College Park, MD, 20742, USA.
Ke H; Department of Mathematics, University of Maryland, College Park, MD, 20742, USA.
Ye Z; Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD, 20740, USA.
Xu Z; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
Chen S; Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Ma T; Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD, 20740, USA. tma0929@umd.edu.

Sci Rep ; 11(1): 3203, 2021 02 05.

Article en En | MEDLINE | ID: mdl-33547332

Asunto(s)

Biomarcadores de Tumor/genética; Genómica; Neoplasias/genética; Transcriptoma; Perfilación de la Expresión Génica; Humanos; Neoplasias/epidemiología; Pronóstico; Modelos de Riesgos Proporcionales; Análisis de Supervivencia

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biomarcadores de Tumor / Genómica / Transcriptoma / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google