Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensiona...

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Bibliographic Details
Main Authors: Lan Shu, Xuehua Li
Format: Article
Language:English
Published: MDPI AG 2008-07-01
Series:Sensors
Subjects:
Manifold learning
Dimensionality reduction
Locally linear embedding
Kernel methods
Support vector machine.
Online Access:http://www.mdpi.com/1424-8220/8/7/4186/

Internet

http://www.mdpi.com/1424-8220/8/7/4186/

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