Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as h...

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Detalles Bibliográficos
Autores principales: Yang, Liying, Liu, Zhimin, Yuan, Xiguo, Wei, Jianhua, Zhang, Junying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5143691/
https://www.ncbi.nlm.nih.gov/pubmed/27999797
http://dx.doi.org/10.1155/2016/4596326

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5143691/
https://www.ncbi.nlm.nih.gov/pubmed/27999797
http://dx.doi.org/10.1155/2016/4596326

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