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 Ski de fond - Accessoires - Fartages bioinformatics and biomedical research.However, most current GCNA algorithms use correlation to build gene co-expression networks and identify modules