Analysis of Gene Expression Data to Predict Genomic Interactions involved in Immune Responses Caused by Dengue Fever
Abstract
Abstract
Dengue fever is a mosquito-borne Aedes genus viral disease affecting to human all over the world. Current several diagnostic methods to find the disease, but no drug treatment for the disease and no validated therapeutic targets for the disease. There are several immune cells involved in antigen–antibody reaction against the viral replication and disease progression, but complete molecular mechanism is remains unknown. Several bioassays to confirm the disease based on pathogenesis, yet there is a need to identify several genes involved in different signaling pathways, pathogenesis and potential drug targets. The peripheral blood mononuclear whole genome gene expression datasets to identify transcriptional gene regulation on immune systems gene signatures to predict clinical significant biomarkers on dengue infection. Using statistical tests and SVM multivariate classifications to identify differentially expressed gene signatures. The results showed in this is differentially expressed genes based on clustering, sub-grouping of datasets that predict biomarkers, and gene–gene interaction network prediction to understand clinically significant bioassays.
Keywords: Dengue virus, dengue fever, microarray, Affymetrix, gene expression, immune system
Cite this Article
Rakesh N.R., Gurumurthy H., Chaitra K.J. Analysis of Gene Expression Data to Predict Genomic Interactions involved in Immune Responses Caused by Dengue Fever. Research & Reviews: A Journal of Bioinformatics. 2017; 4(1): 9–15p.
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