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CATA
2008
13 years 7 months ago
Investigation of Random Forest Performance with Cancer Microarray Data
The diagnosis of cancer type based on microarray data offers hope that cancer classification can be highly accurate for clinicians to choose the most appropriate forms of treatmen...
Myungsook Klassen, Matt Cummings, Griselda Saldana
BMCBI
2008
96views more  BMCBI 2008»
13 years 6 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...
CSB
2005
IEEE
121views Bioinformatics» more  CSB 2005»
13 years 12 months ago
K-means+ Method for Improving Gene Selection for Classification of Microarray Data
Heng Huang, Rong Zhang, Fei Xiong, Fillia Makedon,...
BMCBI
2010
132views more  BMCBI 2010»
13 years 6 months ago
Error margin analysis for feature gene extraction
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...
BMCBI
2010
116views more  BMCBI 2010»
13 years 6 months ago
FiGS: a filter-based gene selection workbench for microarray data
Background: The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene sel...
Taeho Hwang, Choong-Hyun Sun, Taegyun Yun, Gwan-Su...