TY - GEN
T1 - A three-stage method to select informative genes from gene expression data in classifying cancer classes
AU - Mohamad, Mohd Saberi
AU - Omatu, Sigeru
AU - Deris, Safaai
AU - Yoshioka, Michifumi
PY - 2010
Y1 - 2010
N2 - The process of gene selection for the cancer classification faces with a major problem due to the properties of the data such as the small number of samples compared to the huge number of genes, irrelevant genes, and noisy data. Hence, this paper aims to select a near-optimal (small) subset of informative genes that is most relevant for the cancer classification. To achieve the aim, a three-stage method has been proposed. It has three stages: 1) pre-selecting genes using a filter method; 2) optimizing the gene subset using a multi-objective hybrid method; 3) analyzing the frequency of appearance of each gene. By performing experiments on three public gene expression data sets, classification accuracies and the number of selected genes of the proposed method are better than those of other experimented methods and previous works. A list of informative genes in the final gene subsets is also presented for biological usage.
AB - The process of gene selection for the cancer classification faces with a major problem due to the properties of the data such as the small number of samples compared to the huge number of genes, irrelevant genes, and noisy data. Hence, this paper aims to select a near-optimal (small) subset of informative genes that is most relevant for the cancer classification. To achieve the aim, a three-stage method has been proposed. It has three stages: 1) pre-selecting genes using a filter method; 2) optimizing the gene subset using a multi-objective hybrid method; 3) analyzing the frequency of appearance of each gene. By performing experiments on three public gene expression data sets, classification accuracies and the number of selected genes of the proposed method are better than those of other experimented methods and previous works. A list of informative genes in the final gene subsets is also presented for biological usage.
KW - Cancer classification
KW - Component
KW - Gene expression data
KW - Gene selection
KW - Genetic algorithm
KW - Three-stage method
UR - http://www.scopus.com/inward/record.url?scp=77950952766&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950952766&partnerID=8YFLogxK
U2 - 10.1109/ISMS.2010.39
DO - 10.1109/ISMS.2010.39
M3 - Conference contribution
AN - SCOPUS:77950952766
SN - 9780769539737
T3 - ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation
SP - 158
EP - 163
BT - ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation
T2 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010
Y2 - 27 January 2010 through 29 January 2010
ER -
