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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Detalles Bibliográficos
Autores principales: Crisman, Thomas J., Zelaya, Ivette, Laks, Dan R., Zhao, Yining, Kawaguchi, Riki, Gao, Fuying, Kornblum, Harley I., Coppola, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5113897/
https://www.ncbi.nlm.nih.gov/pubmed/27855170
http://dx.doi.org/10.1371/journal.pone.0164649

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5113897/
https://www.ncbi.nlm.nih.gov/pubmed/27855170
http://dx.doi.org/10.1371/journal.pone.0164649

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