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Updated: Jul 22, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support
Sihua Peng1, Qianghua Xu, Xuefeng Bruce Ling
1National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, PR China.
Abstract:
Simultaneous multiclass classification of tumor types is essential for future clinical implementations of microarray-based cancer diagnosis. In this study, we have combined genetic algorithms (GAs) and all paired support vector machines (SVMs) for multiclass cancer identification. The predictive features have been selected through iterative SVMs/GAs, and recursive feature elimination post-processing steps, leading to a very compact cancer-related predictive gene set. Leave-one-out cross-validations yielded accuracies of 87.93% for the eight-class and 85.19% for the fourteen-class cancer classifications, outperforming the results derived from previously published methods.
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