In the era of post-genomics, computational analysis of genomics and transcriptomics to understand the non-coding microRNA (miRNA) based regulated networks in autoimmune diseases like psoriasis is an uphill task. We have herein approached the challenge on the basis of four computational approaches: Top-down - miRNA based associated regulation; Bottom-up - miRNA based expressed and co expressed regulation; Direct - miRNA based Pharmacogenomic regulation; Indirect - miRNA based pharmacovarient regulation. The outcomes of the present study on the identification of a specific miRNA has-miR-125 as a potential biomarker for treating psoriasis and the regulatory network involves MTHFR as a potential target gene and AHR as a potential transcription Factor. Finally the regulatory network initiates the cascade of pathogenesis by the activation CCR5, IL23, HTL-1 and KR23 and the proposed mathematical model gives a clear understanding of pathogenesis. Validation of the mathematical model requires more challenge experiments under various conations from patients of dynamic group. The computational analysis is an initiative to redefine and have a better understanding towards the pathogenesis of Psoriasis prior towards the identification of a theronastic (diagnostic and therapeutic) biomarker. Biomarker based research and GWAS studies in autoimmune disorders like Psoriasis took a great dimension towards exploring novel targets in the era of post genomics.

Keywords: Autoimmune Diseases, Computational Analysis, MicroRNA, Pharmacogenomics and Psoriasis.