Ensemble outlier detection and gene selection in triple-negative breast cancer data

BACKGROUND: Learning accurate models from ‘omics data is bringing many challenges due to their inherent high-dimensionality, e.g. the number of gene expression variables, and comparatively lower sample sizes, which leads to ill-posed inverse problems. Furthermore, the presence of outliers, either ex...

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Detalles Bibliográficos
Autores principales: Lopes, Marta B., Veríssimo, André, Carrasquinha, Eunice, Casimiro, Sandra, Beerenwinkel, Niko, Vinga, Susana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5936001/
https://www.ncbi.nlm.nih.gov/pubmed/29728051
http://dx.doi.org/10.1186/s12859-018-2149-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5936001/
https://www.ncbi.nlm.nih.gov/pubmed/29728051
http://dx.doi.org/10.1186/s12859-018-2149-7

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