Abstract
Genes need to be investigated either in Gene Interaction Network or in a DNA microarray gene expression data to understand the role they play in complex diseases like cancer. The prioritized genes can help us to know the molecular mechanism, as well as to discover the promising candidates of cancer. Several gene ranking algorithms already have been proposed that produces the top ranked genes according to their importance with respect to a particular disease. In this work, we have developed one Genetic Algorithm (GA) based algorithm, MicroarrayGA, to rank the genes responsible for a particular cancer to occur. The whole research works on six datasets like Colorectal Cancer, Diffuse Large B-Cell Lymphoma, Pediatric Immune Thrombocytopenia (ITP), Small Cell Lung Cancer (SCLC), Breast Cancer and Prostate Cancer, publicly available from NCBI (National Center for Biotechnology Information) online repository. We have validated the outcome of the proposed algorithm by classification step using Support Vector Machine (SVM) classifier and we have also compared the results of MicroarrayGA with three existing methods on the basis of percentage of accuracy, precision, recall, F1-Score and G-Mean metrics.
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Saha, S., Das, P., Ghosh, A., Dey, K.N. (2018). Ranking of Cancer Mediating Genes: A Novel Approach Using Genetic Algorithm in DNA Microarray Gene Expression Dataset. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_13
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