Incorporating biological information in sparse principal component analysis with application to genomic data

Incorporating biological information in sparse principal component analysis with application to genomic data

Abstract Background Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in...

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Bibliographic Details
Main Authors: Ziyi Li, Sandra E. Safo, Qi Long
Format: Article
Language:English
Published: BMC 2017-07-01
Series:BMC Bioinformatics
Subjects:
Principal component analysis
Sparsity
Structural information
Genomic data
Online Access:http://link.springer.com/article/10.1186/s12859-017-1740-7

Internet

http://link.springer.com/article/10.1186/s12859-017-1740-7

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