Method- The total RNA microarray processed data from GEO for Multiple sclerotic patients was comprehensively analyzed to find out underlying differences between Grey Matter lesions, Normal appearing Grey Matter and Control Grey matter at the transcriptomics level. We performed various bioinformatics analyses on transcriptional profiles of a total 184 Total-RNA-Seq samples including 105 Normal appearing Grey Matter NAMG, 37 Grey Matter lesions GML, and 42 Healthy controls that were obtained from the NCBI Bio-Project PRJNA543111.
Results- Conclusively, our study depicted significant differences in the gene expression patterns between GML and CG samples. As a result, 20736 genes , padj. value less than 0.05, log2 fold change 0.5 were found to be significantly differentially expressed among these conditions based on differential gene expression analysis. This study discovers new 12 genes like OR10A7, OR11L1, OR2AG1, OR2C3, ORT25, OR4D6, OR52E4, 0R5D16, OR5K1, OR7D4, OR8K1, and ORAI3 as the key features that may substantially contribute to the loss of Olfactory senses in MS patients. Our study also proposes the involvement of Protein Kinase-A in the pathogenesis of Multiple sclerosis. Eventually, the results presented here reveal new insights into MS and its relation with the biological pathways especially Olfactory transduction and Hematopoietic stem cell lineage pathways.

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The Bioinformatics fellowship is a structured program that guides students through various areas of Big Data Bioinformatics Research using practical examples. During this program, we go through several high-quality research publications and learn about applications of computational biology in projects these publications describe. This kind of an experience allows beginners to try computational biology techniques on public domain data, making it possible to work with large files and extract meaningful information from patient samples, animal models, cell-lines, and microbiota. The program provides support and mentorship, therefore it is an intensive research program involving training tasks, access to our online sessions and a guide on the implementation of learned skills to proposed research ideas.

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