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Identification of an Efficient Gene Expression Panel for Glioblastoma Classification
We present here a novel genetic algorithm-based random forest (GARF) modeling technique that enables a reduction in the complexity of large gene disease signatures to highly accurate, greatly simplified gene panels. When applied to 803 glioblastoma multiforme samples, this method allowed the 840-gen...
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| izdano v: | PLoS One |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Public Library of Science
2016
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| Teme: | |
| Online dostop: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5113897/ https://ncbi.nlm.nih.gov/pubmed/27855170 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0164649 |
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