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

Portraying the Expression Landscapes of B-CellLymphoma-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...

Full description

Bibliographic Details
Main Authors: Lydia Hopp, Kathrin Lembcke, Hans Binder, Henry Wirth
Format: Article
Language:English
Published: MDPI AG 2013-12-01
Series:Biology
Subjects:
co-regulated genes
molecular function
network analysis
machine learning
classifying cancer
Online Access:http://www.mdpi.com/2079-7737/2/4/1411

Internet

http://www.mdpi.com/2079-7737/2/4/1411

Similar Items