Identifying MicroRNA Markers From Expression Data: A Network Analysis Based Approach
The identification of biomarkers is very important to know the presence or severity of a particular disease state in the patient body. According to the latest studies on miRNAs and their behaviors, it is known to us that miRNAs involve in the regulation mechanism of several biological processes. Sometimes the abnormal change in miRNA expressions in different conditions may lead to malignant growth in tissues. In this article, our proposed approach not only helps to detect differentially coexpressed modules but also helps to identify biomarker candidates from those modules. The proposed algorithm uses the WCGNA software package to explore coexpression profiles of the miRNAs. The algorithm has been applied to existing miRNA datasets to point out the miRNA markers. Then, biological validation analysis has been performed for the obtained miRNA markers.
KeywordsMicroRNA marker Microarray analysis Differentially coexpressed network Topological overlap Intramodular connectivity MiRNA-target interaction Carcinomas
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