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Computational Analysis of Pharmacogenomic Based Regulatory Network in Psoriasis: An Approach of Systems Biology to Initiate the Discovery of Systemic Biomarkers to Treat Psoriasis

Publication Type : Journal Article

Publisher : Syst Comput Biol J

Source : Syst Comput Biol J

Campus : Coimbatore

Center : Computational Engineering and Networking

Year : 2018

Abstract : In the era of post genomics, performing a computational analysis to understand the pharmacogenomic based regulation of Psoriasis with respect to the principles of data mining and constructing a regulatory network with respect to the principles of systems biology and analyzing the network with respect to the principles of test statistic remains a challenging task to execute. The challenge was approached by identifying the associated genes of Psoriasis from PharmGkb and it was followed by identifying the associated regulators (MicroRNAs and Transcription Factors) from PharmacomiR/RegNetworks. Finally the regulatory networks were analyzed by the statistical measures. Introduction Psoriasis is a disorder mediated by the immune system by making certain faulty signals in the human body. It’s still a belief that psoriasis can be developed under the specified conditions, ie “when the immune system signals the body to accelerate the growth of skin cells. Normally, skin cells get matured from the surface of the skin for every 28-30 days. In case of psoriasis, the skin cells mature in 3-6 days. Instead of being in the shed, the cells in the skin get piled up to cause the visible lesions. It was also found that the genes that cause psoriasis can determine the reaction of a person’s immune system. These genes can either cause psoriasis or other conditions which are immune-mediated like Type-I Diabetes or rheumatoid arthritis.

Cite this Research Publication : H Anandaram, Computational Analysis of Pharmacogenomic Based Regulatory Network in Psoriasis: An Approach of Systems Biology to Initiate the Discovery of Systemic Biomarkers to Treat Psoriasis - Syst Comput Biol J, 2018

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