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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39 For more details click here
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2018: 95.39
For more details click here

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Original Research Articles

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 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2017.6(8): 185-193
DOI: https://doi.org/10.20546/ijcmas.2017.608.026


Differential Gene Expression Analysis of Prostate Cancer for Biomarkers and Potential Drug Targets Identification
Mujeeb Rahiman Thayyil Kunhumuhammed1, Ashvini Desai2, Inamul Hasan Madar3* and Iftikhar Aslam Tayubi4
1Department of Computer Science, Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Jeddah Kingdom of Saudi Arabia
2Department of Bioinformatics, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India
3Department of Biotechnology and Genetic Engineering and Department of Biochemistry, Bharathidasan University, Tiruchirappalli, 620024, Tamil Nadu, India
4Faculty of Computing and Information Technology, Rabigh King Abdul-Aziz University, Jeddah, 21911, Saudi Arabia
*Corresponding author
Abstract:

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.


Keywords: Prostate Cancer, Microarray data analysis, Bioconductor, gene ontology, DAVID, Principal Component Analysis.
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How to cite this article:

Mujeeb Rahiman Thayyil Kunhumuhammed, Ashvini Desai, Inamul Hasan Madar and Iftikhar Aslam Tayubi. 2017. Differential Gene Expression Analysis of Prostate Cancer for Biomarkers and Potential Drug Targets identification.Int.J.Curr.Microbiol.App.Sci. 6(8): 185-193. doi: https://doi.org/10.20546/ijcmas.2017.608.026