National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Prostate Cancer is one of the leading causes of malignancy among men and is a complex multifaceted and biologically heterogeneous disease. The in silico Microarray data analysis produces the gene expression profiling of Prostate Cancer and it has also been shown to provide the molecular phenotyping that determines the characterizing of various stages of the cancer. In the current study, we analyzed the normal Prostate epithelial cells (PrEC) and Prostate cell line (LnCPa) data. For preprocessing we performed data normalization using the Reliability, Maintainability, and Availability (RMA) algorithm in the R (v-3.2.3) and limma package of the Bioconductor was used to identify the differentially expressed genes (DEGs), using the value ≤0.05 and fold change ≥ 2 to ≤ -2. The gene ontology and gene set enrichment analysis was performed using the DAVID online tool. Current study revealed 140 DEGs obtained by the Gene ontology and pathway analyses in DAVID using the filtered genes that had principle pathways targeting Prostate Cancer.
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