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 identify modules with highly correlated genes. There is a need to look beyond correlation ... https://darthomes.shop/product-category/coasters/
Generalized gene co-expression analysis via subspace clustering using low-rank representation
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