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An Improved gSVM-SCADL2 with Firefly Algorithm for Identification of Informative Genes and Pathways

Chan, Weng Howe and Mohd Saberi , Mohamad and Safaai , Deris and Corchado, Juan Manuel and Omatu, Sigeru and Zuwairie, Ibrahim and Shahreen, Kasim (2016) An Improved gSVM-SCADL2 with Firefly Algorithm for Identification of Informative Genes and Pathways. International Journal of Bioinformatics Research and Applications, 12 (1).

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Abstract

Incorporation of pathway knowledge into microarray analysis has been favoured by researchers owing to the improved biological interpretation of the analysis outcome. However, most of the pathway data are manually curated without specific biological context. Inclusion of non-informative genes in the analysis of context specific microarray data could lead to classifier with poor discriminative power. Thus, one of the main challenges is how to effectively identify informative genes from the pathway data. This paper proposes a firefly optimised penalised support vector machine with SCADL2 penalty function (SVM-SCADL2-FFA) in optimising tuning parameters for each pathway for efficient identification of informative genes and pathways. Experiments are done on lung cancer and gender data sets. Tenfold CV is used to evaluate the performance in terms of accuracy, specificity, sensitivity and F-score. The identified informative genes are validated through online databases. Our proposed method shows consistent improvements compared to previous works.

Item Type: Article
Uncontrolled Keywords: pathway-based microarray analysis, gene selection, penalised SVM, support vector machines,bioinformatics, artificial intelligence, firefly algorithm, genes, pathways, lung cancer, gender
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 28 Dec 2016 01:18
Last Modified: 22 Aug 2017 07:12
URI: http://umpir.ump.edu.my/id/eprint/13631
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