Feature selection of gene expression data for Cancer classification using double RBF-kernels

Feature selection of gene expression data for Cancer classification using double RBF-kernels

Abstract Background Using knowledge-based interpretation to analyze omics data can not only obtain essential information regarding various biological processes, but also reflect the current physiological status of cells and tissue. The major challenge to analyze gene expression data, with a large nu...

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Bibliographic Details
Main Authors: Shenghui Liu, Chunrui Xu, Yusen Zhang, Jiaguo Liu, Bin Yu, Xiaoping Liu, Matthias Dehmer
Format: Article
Language:English
Published: BMC 2018-10-01
Series:BMC Bioinformatics
Subjects:
Clustering
Gene expression
Cancer classification
Feature selection
Data mining
Online Access:http://link.springer.com/article/10.1186/s12859-018-2400-2

Internet

http://link.springer.com/article/10.1186/s12859-018-2400-2

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