Halagan, Michael2017-11-272017-11-272017-08https://hdl.handle.net/11299/191284University of Minnesota M.S. thesis.August 2017. Major: Biomedical Informatics and Computational Biology. Advisor: Abeer Madbouly. 1 computer file (PDF); 57 pages + 2 supplementary files.Hematopoietic Stem Cell Transplantation (HSCT) is a curative therapy for multiple malignant and non-malignant blood disorders. Multiple opportunities exist for facilitating and improving the accuracy of matching potential donors with patients in need of HSCT. The global donor pool does not adequately represent many regions of the world; therefore, donor searches would benefit from the haplotype analysis and modeling of underserved populations. Utilizing sequence data in matching algorithms also has potential to improve HSCT for patients in need. We developed the Gene Feature Enumeration (GFE) ecosystem to supplement the current HLA nomenclature by retaining all sequence data, hence enhancing matching precision. To improve the global donor pool, we performed a haplotype frequency analysis and registry modeling on the Ezer Mizion registry in Israel. Combining all these bioinformatics tools provides invaluable resources for unrelated donor registries to help serve HSCT patients worldwide.enFrequenciesHematopoietic Stem Cell TransplantationHLAThesis or Dissertation