Discovering differences in gender-related skeletal muscle aging through the majority voting-based identification of differently expressed genes

Dreder, Abdouladeem, Tahir, Muhammad, Seker, Huseyin and Anwar, Naveed (2016) Discovering differences in gender-related skeletal muscle aging through the majority voting-based identification of differently expressed genes. International Journal on Bioinformatics & Biosciences, 6 (2). pp. 1-14. ISSN 1839-9614

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Abstract

Understanding gene function (GF) is still a significant challenge in system biology. Previously, several machine learning and computational techniques have been used to understand GF. However, these previous attempts have not produced a comprehensive interpretation of the relationship between genes and differences in both age and gender. Although there are several thousands of genes, very few differentially expressed genes play an active role in understanding the age and gender differences. The core aim of this study is to uncover new biomarkers that can contribute towards distinguishing between male and female according to the gene expression levels of skeletal muscle (SM) tissues. In our proposed multi-filter system (MFS), genes are first sorted using three different ranking techniques (t-test, Wilcoxon and Receiver Operating Characteristic (ROC)). Later, important genes are acquired using majority voting based on the principle that combining multiple models can improve the generalization of the system. Experiments were conducted on Micro Array gene expression dataset and results have indicated a significant increase in classification accuracy when compared with existing system.

Item Type: Article
Uncontrolled Keywords: Multi-Filter System, Filter Techniques, Micro Array Gene Expression, Skeletal muscle
Subjects: C100 Biology
C400 Genetics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Naveed Anwar
Date Deposited: 20 Sep 2016 08:30
Last Modified: 06 Sep 2017 19:07
URI: http://nrl.northumbria.ac.uk/id/eprint/27774

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