Cargando…
Gene selection and classification for cancer microarray data based on machine learning and similarity measures
BACKGROUND: Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. A...
Autores principales: | Liu, Qingzhong, Sung, Andrew H, Chen, Zhongxue, Liu, Jianzhong, Chen, Lei, Qiao, Mengyu, Wang, Zhaohui, Huang, Xudong, Deng, Youping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287491/ https://www.ncbi.nlm.nih.gov/pubmed/22369383 http://dx.doi.org/10.1186/1471-2164-12-S5-S1 |
Ejemplares similares
-
Feature Selection and Classification of MAQC-II Breast Cancer and Multiple Myeloma Microarray Gene Expression Data
por: Liu, Qingzhong, et al.
Publicado: (2009) -
Comparison of feature selection and classification for MALDI-MS data
por: Liu, Qingzhong, et al.
Publicado: (2009) -
Supervised learning-based tagSNP selection for genome-wide disease classifications
por: Liu, Qingzhong, et al.
Publicado: (2008) -
A distribution-free convolution model for background correction of oligonucleotide microarray data
por: Chen, Zhongxue, et al.
Publicado: (2009) -
A gene selection method for GeneChip array data with small sample sizes
por: Chen, Zhongxue, et al.
Publicado: (2011)