Gene Selection for Cancer Classification through Ensemble of Methods
- Artur Wilinski,
- Stanisław Osowski,
- Krzysztof Siwek
The paper develops the methods of selection of the most important gene sequence on the basis of the gene expression microarray, corresponding to different types of cancer. Special two stage strategy of selection has been proposed. In the first stage we apply few different methods of assessment of the importance of genes. Each method stresses different aspects of the problem. In the second stage the selected genes are compared and the genes chosen most frequently by all methods of selection are treated as the most important and representative for the particular type of problem. The results of selection are analyzed using PCA and the selected genes form the input to the SVM classifier recognizing the classes of cancer. The numerical experiments confirm the efficiency of the proposed approach.
- Record ID
- Kolehmainen Mikko, Mikko Kolehmainen Toivanen Pekka, Pekka Toivanen Beliczyński Bartłomiej Bartłomiej Beliczyński (eds.): Adaptive and Natural Computing Algorithms, Lecture Notes In Computer Science, no. 5495, 2009, Springer Berlin Heidelberg, ISBN 978-3-642-04920-0, 978-3-642-04921-7
- Keywords in English
- Algorithm Analysis and Problem Complexity, Artificial Intelligence (incl. Robotics), Computational Biology/Bioinformatics, Computation by Abstract Devices, feature selection, gene expression array, Programming Techniques, Software Engineering, SVM classification
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