Generalized gene co-expression analysis via subspace clustering using low-rank representation

Generalized gene co-expression analysis via subspace clustering using low-rank representation

Abstract Background Gene Co-expression Network Analysis (GCNA) helps identify gene modules with potential biological functions and has become a popular method in bioinformatics and biomedical research. However, most current GCNA algorithms use correlation to build gene co-expression networks and ide...

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Bibliographic Details
Main Authors: Tongxin Wang, Jie Zhang, Kun Huang
Format: Article
Language:English
Published: BMC 2019-05-01
Series:BMC Bioinformatics
Subjects:
Gene co-expression network analysis
Subspace clustering
Low-rank representation
Online Access:http://link.springer.com/article/10.1186/s12859-019-2733-5

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