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Microarray technology has shifted to a new era in molecular classification, however, interpreting gene expression data to remain a challenging issue due to their innate nature of "high dimensional low sample size". Furthermore, this data is often overwhelmed, overfitting and confused by the complexity of data analysis. Small sample size and a large number of variables to be analysed posed significant challenges during data analysis, mainly in learning network structure. Moreover, the ability to study the gene interactions that form tumour growth is a great difficulty to computational biology...