eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes
Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checkerb...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2014-01-01
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| Series: | Cancer Informatics |
| Online Access: | https://doi.org/10.4137/CIN.S13777 |