Emile Rugamika Chimusa
Accepting PhD Students
1. Next-generation computational method for Genomics Risk Assessment and Stratification in multi-way admixed and structured populations.
2. Developing improved statistical and computational models for the association tests of genetic variation versus drug response, genetic variation versus individualised dosage regimens of potentially toxic drugs accounting different environment factors.
3. Leveraging evolutionary convergence, polygeneticity and population structure in Bacterial Genome-wide association studies.
4. Computational model for pinpointing accurately individual's ancestry along its genome or on a specific chromosomal region to cope with populations that have a complex admixture history and adaptation event.
5. Computational models for leveraging cross-population gene/sub-network meta-analysis to recover disease association signal risk, cross-population gene/sub-network drug responses and regulations in homogeneous or recently admixed populations.
Willing to speak to media