Amr Badr

Citation:

M.korayem, Wabo hamad, A.Badr, and K.moustafa, "Informative Gene Selection for Clustering Gene Expression Data Using a Hybrid GA/CSA", International Journal of Computational Intelligence and Applications (IJCIA), vol. 11, issue 3, pp. 23-29, 2007.

Abstract:

In this paper, a hybrid genetic-clonal selection algorithm is presented to select informative genes from DNA Microarray data. The proposed approach can be used for clustering or classification of the high dimensional gene expression data. Clustering analysis of genes obtained with the proposed method is applied on gene expression data. The main features for the proposed method concerns the main force of the evolutionary process for the GA which is crossover operator and one of main principles of the immune system which is the clonal selection principle. The effectiveness of the proposed method is assessed using three well-known data sets of cancer, showing highly competitive results.