Selecting informative genes from microarray data by using a cyclic GA-based method

Mohd Saberi Mohamad; Sigeru Omatu; Safaai Deris; Michifumi Yoshioka

doi:10.1109/ISMS.2010.14

Selecting informative genes from microarray data by using a cyclic GA-based method

Mohd Saberi Mohamad
, Sigeru Omatu
, Safaai Deris
, Michifumi Yoshioka

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Microarray data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. The main problem that needs to be addressed is the selection of a small subset of genes from the thousands of genes in the data that contributes to a cancer disease. This selection process is difficult due to the availability of a small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes a cyclic method based on genetic algorithms (GA) to select a near-optimal (small) subset of informative genes that is relevant for cancer classification. The performance of the proposed method was evaluated by three benchmark microarray data sets and obtained encouraging results as compared with other experimented methods and previous related works.

Original language	English
Title of host publication	ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation
Pages	15-20
Number of pages	6
DOIs	https://doi.org/10.1109/ISMS.2010.14
Publication status	Published - 2010
Externally published	Yes
Event	UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010 - Liverpool, United Kingdom Duration: Jan 27 2010 → Jan 29 2010

Publication series

Name	ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation

Conference

Conference	UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010
Country/Territory	United Kingdom
City	Liverpool
Period	1/27/10 → 1/29/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Component
Cyclic approach
Gene selection
Genetic algorithms
Hybrid method
Microarray data

ASJC Scopus subject areas

General Computer Science
Theoretical Computer Science

Access to Document

10.1109/ISMS.2010.14

Cite this

Mohamad, M. S., Omatu, S., Deris, S., & Yoshioka, M. (2010). Selecting informative genes from microarray data by using a cyclic GA-based method. In ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation (pp. 15-20). Article 5416131 (ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation). https://doi.org/10.1109/ISMS.2010.14

Selecting informative genes from microarray data by using a cyclic GA-based method. / Mohamad, Mohd Saberi; Omatu, Sigeru; Deris, Safaai et al.
ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation. 2010. p. 15-20 5416131 (ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mohamad, MS, Omatu, S, Deris, S & Yoshioka, M 2010, Selecting informative genes from microarray data by using a cyclic GA-based method. in ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation., 5416131, ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, pp. 15-20, UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010, Liverpool, United Kingdom, 1/27/10. https://doi.org/10.1109/ISMS.2010.14

Mohamad MS, Omatu S, Deris S, Yoshioka M. Selecting informative genes from microarray data by using a cyclic GA-based method. In ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation. 2010. p. 15-20. 5416131. (ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation). doi: 10.1109/ISMS.2010.14

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abstract = "Microarray data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. The main problem that needs to be addressed is the selection of a small subset of genes from the thousands of genes in the data that contributes to a cancer disease. This selection process is difficult due to the availability of a small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes a cyclic method based on genetic algorithms (GA) to select a near-optimal (small) subset of informative genes that is relevant for cancer classification. The performance of the proposed method was evaluated by three benchmark microarray data sets and obtained encouraging results as compared with other experimented methods and previous related works.",

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Selecting informative genes from microarray data by using a cyclic GA-based method

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this