Classifying subtypes of acute lymphoblastic leukemia using silhouette statistics and genetic algorithms.
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[1] Ru-Sheng Liu,et al. Pattern classification in DNA microarray data of multiple tumor types , 2006, Pattern Recognit..
[2] Xuefeng Bruce Ling,et al. Multiclass cancer classification and biomarker discovery using GA-based algorithms , 2005, Bioinform..
[3] Tao Li,et al. A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression , 2004, Bioinform..
[4] J. M. Deutsch,et al. Evolutionary algorithms for finding optimal gene sets in microarray prediction , 2003, Bioinform..
[5] Patrick Tan,et al. Genetic algorithms applied to multi-class prediction for the analysis of gene expression data , 2003, Bioinform..
[6] J. Downing,et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. , 2002, Cancer cell.
[7] S. Dudoit,et al. Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data , 2002 .
[8] Thomas A. Darden,et al. Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method , 2001, Bioinform..
[9] M. Ringnér,et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks , 2001, Nature Medicine.
[10] Nello Cristianini,et al. Support vector machine classification and validation of cancer tissue samples using microarray expression data , 2000, Bioinform..
[11] Ash A. Alizadeh,et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.
[12] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[13] P. Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .