File Entry: Multi-Objective Optimization Using Genetic Algorithm for Gene Selection from Microarray Data

Created: 2012-05-11 02:23:50
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Version created on: 2012-05-11 02:23:50

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 Microarray technology has been increasingly used

in cancer research because of its potential for
measuring expression levels of thousands of genes
simultaneously in tissue samples. It is used to collect
the information from tissue samples regarding gene
expression differences that could be useful for cancer
classification. However, this classification task faces
many challenges due to availability of a smaller
number of samples compared to the huge number of
genes, and many of the genes are not relevant to the
classification. It has been shown that selecting a small
subset of genes can lead to an improved accuracy of
the classification. Hence, this paper proposes a
solution to the problem of gene selection by using a
multi-objective approach in genetic algorithm. This
approach is experimented on two microarray data sets
such as Lung cancer and Mixed-Lineage Leukemia
cancer. It obtains encouraging result on those data
sets as compared with an approach that uses singleobjective

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