Cargando…
Dynamic classification using case-specific training cohorts outperforms static gene expression signatures in breast cancer
The molecular diversity of breast cancer makes it impossible to identify prognostic markers that are applicable to all breast cancers. To overcome limitations of previous multigene prognostic classifiers, we propose a new dynamic predictor: instead of using a single universal training cohort and an...
Autores principales: | Győrffy, Balázs, Karn, Thomas, Sztupinszki, Zsófia, Weltz, Boglárka, Müller, Volkmar, Pusztai, Lajos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354298/ https://www.ncbi.nlm.nih.gov/pubmed/25274406 http://dx.doi.org/10.1002/ijc.29247 |
Ejemplares similares
-
Current composite-feature classification methods do not outperform simple single-genes classifiers in breast cancer prognosis
por: Staiger, Christine, et al.
Publicado: (2013) -
MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction
por: Menyhart, Otília, et al.
Publicado: (2021) -
Correction: MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction
por: Menyhart, Otília, et al.
Publicado: (2022) -
Supporting grant reviewers through the scientometric ranking of applicants
por: Győrffy, Balázs, et al.
Publicado: (2023) -
Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models
por: Sztupinszki, Zsófia, et al.
Publicado: (2016)