Co-ABC : correlation artificial bee colony algorithm for biomarker gene discovery using gene expression profile
Author
Source
Saudi Journal of Biological Sciences
Issue
Vol. 25, Issue 5 (31 Jul. 2018), pp.895-903, 9 p.
Publisher
Publication Date
2018-07-31
Country of Publication
Saudi Arabia
No. of Pages
9
Main Subjects
Abstract EN
In this paper, we propose a new hybrid method based on Correlation-based feature selection method and Artificial Bee Colony algorithm,namely Co-ABC to select a small number of relevant genes for accurate classification of gene expression profile.
The Co-ABC consists of three stages which are fully cooperated: The first stage aims to filter noisy and redundant genes in high dimensionality domains by applying Correlation-based feature Selection (CFS) filter method.
In the second stage, Artificial Bee Colony (ABC) algorithm is used to select the informative and meaningful genes.
In the third stage, we adopt a Support Vector Machine (SVM) algorithm as classifier using the preselected genes form second stage.
The overall performance of our proposed Co-ABC algorithm was evaluated using six gene expression profile for binary and multi-class cancer datasets.
In addition, in order to proof the efficiency of our proposed Co-ABC algorithm, we compare it with previously known related methods.
Two of these methods was reimplemented for the sake of a fair comparison using the same parameters.
These two methods are: Co- GA, which is CFS combined with a genetic algorithm GA.
The second one named Co-PSO, which is CFS combined with a particle swarm optimization algorithm PSO.
The experimental results shows that the proposed Co-ABC algorithm acquire the accurate classification performance using small number of predictive genes.
This proofs that Co-ABC is a efficient approach for biomarker gene discovery using cancer gene expression profile.
American Psychological Association (APA)
al-Shamlan, Halah Muhammad. 2018. Co-ABC : correlation artificial bee colony algorithm for biomarker gene discovery using gene expression profile. Saudi Journal of Biological Sciences،Vol. 25, no. 5, pp.895-903.
https://search.emarefa.net/detail/BIM-838489
Modern Language Association (MLA)
al-Shamlan, Halah Muhammad. Co-ABC : correlation artificial bee colony algorithm for biomarker gene discovery using gene expression profile. Saudi Journal of Biological Sciences Vol. 25, no. 5 (Jul. 2018), pp.895-903.
https://search.emarefa.net/detail/BIM-838489
American Medical Association (AMA)
al-Shamlan, Halah Muhammad. Co-ABC : correlation artificial bee colony algorithm for biomarker gene discovery using gene expression profile. Saudi Journal of Biological Sciences. 2018. Vol. 25, no. 5, pp.895-903.
https://search.emarefa.net/detail/BIM-838489
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 902-903
Record ID
BIM-838489