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» On the Effectiveness of Gene Selection for Microarray Classi...
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AIME
2009
Springer
13 years 11 months ago
Effect of Background Correction on Cancer Classification with Gene Expression Data
This paper empirically compares six background correction methods aimed at removing unspecific background noise of the overall signal level measured by a scanner across microarrays...
Adelaide Freitas, Gladys Castillo, Ana São ...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BMCBI
2006
201views more  BMCBI 2006»
13 years 7 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
IDEAL
2005
Springer
14 years 29 days ago
A Comparative Study of Two Novel Predictor Set Scoring Methods
Due to the large number of genes measured in a typical microarray dataset, feature selection plays an essential role in tumor classification. In turn, relevance and redundancy are ...
Chia Huey Ooi, Madhu Chetty
BIRD
2008
Springer
110views Bioinformatics» more  BIRD 2008»
13 years 9 months ago
SVM-Based Local Search for Gene Selection and Classification of Microarray Data
Abstract. This paper presents a SVM-based local search (SVM-LS) approach to the problem of gene selection and classification of microarray data. The proposed approach is highlighte...
Jose Crispin Hernandez Hernandez, Béatrice ...