A New Hybrid and Ensemble Gene Selection Approach with an Enhanced Genetic Algorithm for Classification of Microarray Gene Expression Values on Leukemia Cancer

Authors

Mehmet Bilen^{1, *,} , Ali H. Işik^2, , Tuncay Yiğit^3,

¹Golhisar School of Applied Sciences, Mehmet Akif Ersoy University, Burdur, Turkey

²Faculty of Engineering and Architecture, Mehmet Akif Ersoy University, Burdur, Turkey

³Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey

^*Corresponding author. Email: mbilen@mehmetakif.edu.tr

DOI

10.2991/ijcis.d.200928.001How to use a DOI?

Keywords

Ensemble approach genetic algorithm; Hybrid algorithm microarray leukemia gene selection; Cancer classification

Abstract

Leukemia cancer, like other types of cancer, is a deadly health condition that threatens the lives of many people around the world. Micro array data are used extensively to reveal the gene-cancer as well as gene–gene relationships of Leukemia cancer due to the fact that it allows the expression value of thousands of genes to be revealed at once. However, the size of the high-dimensional data that the micro arrays accommodate makes it difficult to work with these data. In this study, a new approach was suggested in order to classify the micro arrays of leukemia cancer in a more efficient way by reducing the data size choosing the significant genes. This approach includes two steps: the ensemble step and the hybrid step. In the first step, a gene filtration process is carried out by creating an ensemble gene selection algorithm through Fisher correlation score, Wilcoxon rank sum, and information gain methods. In the second step, the feature selection phase step, the most successful genes among these genes are revealed by using an enhanced genetic algorithm. As a result of the classification process, the leave one out cross validation (LOOCV), 5-fold, and 10-fold cross validation results were found 100%, 98.57, and 97.14, respectively also 100% accuracy was obtained by 2 genes.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Mehmet Bilen
AU  - Ali H. Işik
AU  - Tuncay Yiğit
PY  - 2020
DA  - 2020/10/06
TI  - A New Hybrid and Ensemble Gene Selection Approach with an Enhanced Genetic Algorithm for Classification of Microarray Gene Expression Values on Leukemia Cancer
JO  - International Journal of Computational Intelligence Systems
SP  - 1554
EP  - 1566
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200928.001
DO  - 10.2991/ijcis.d.200928.001
ID  - Bilen2020
ER  -