Portraying the Expression Landscapes of B-Cell Lymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes

We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene expression data of more than 200 mature aggressive B-cell lymphoma patients. The method portrays each sa...

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Detalles Bibliográficos
Autores principales: Hopp, Lydia, Lembcke, Kathrin, Binder, Hans, Wirth, Henry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2013
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009791/
https://www.ncbi.nlm.nih.gov/pubmed/24833231
http://dx.doi.org/10.3390/biology2041411

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009791/
https://www.ncbi.nlm.nih.gov/pubmed/24833231
http://dx.doi.org/10.3390/biology2041411

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