Biomedical research have been revolutionized by recent technological advances, both in the fields of molecular biology and computer science, turning the biomolecular and genetic research into “big data science”. One of the main objectives have been to improve our understanding of complex human diseases. Among those diseases, multiple sclerosis (MS) is considered as one of the most common. MS is a chronic autoimmune disease that cause inflammation and damage to the central nervous system. In this study, a set of bioinformatics analyses have been conducted on SNP data, as an initial step to gain more information prior to an upcoming genotyping project. The results showed extensive regulatory properties for the 761 selected SNPs, which is consistent with current scientific knowledge, and also identified another 332 SNPs in linkage to these. However, during the study some issues have also been identified, which need to be addressed going forward.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-129423 |
| Date | January 2016 |
| Creators | Söderholm, Simon |
| Publisher | Linköpings universitet, Institutionen för fysik, kemi och biologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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