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ESANN
2006
11 years 9 months ago
Selection of more than one gene at a time for cancer prediction from gene expression data
A new gene selection method capable of selecting more than one gene at a time is introduced. This characteristic contrasts it with almost all known methods assuming that there are ...
Oleg Okun, Nikolay G. Zagoruiko, Alexessander Alve...
BMCBI
2010
123views more  BMCBI 2010»
11 years 8 months ago
Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
12 years 1 months ago
A Robust Meta-classification Strategy for Cancer Diagnosis from Gene Expression Data
One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combi...
Gabriela Alexe, Gyan Bhanot, Babu Venkataraghavan,...
BMCBI
2006
122views more  BMCBI 2006»
11 years 8 months ago
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
BMCBI
2008
128views more  BMCBI 2008»
11 years 8 months ago
Improving the prediction accuracy in classification using the combined data sets by ranks of gene expressions
Background: The information from different data sets experimented under different conditions may be inconsistent even though they are performed with the same research objectives. ...
Ki-Yeol Kim, Dong Hyuk Ki, Hei-Cheul Jeung, Hyun C...
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