Prof. Emile R. Chimusa is an internationally recognised computational population genomics and bioinformatics researcher and an experienced educator. He has recently joined Northumbria from the University of Cape Town, where he served as Associate Professor and Programme director of PGDip/MSc/PhD in Computational Health Informatics and Honours in Human Genetics and Forensic Genetics.
He has been a part of a wide array of International Research Consortiums that he has received both research and industry focused funding from the South African National Research Foundation, South African Council for Scientific and Industrial Research, Newton Fund, Canadian International Development Fund, NIH, The Wellcome Trust and Health~Holland. In total, he has received over £17.7 million in research funding as PI or Co-investigator. His research has been published in high-impact international journals and presented both at major scientific conferences and in broadcast, print, and web-based media worldwide. He has a record of accomplishment in designing and developing Computational and Bioinformatics tools ().
My research has a focus on methodologies of improving the analysis of large-scale genomic studies such as genome-wide association, fine-mapping studies, admixture mapping, genomics of mixed ancestry populations and analysing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. My interest is to unlock genomics in healthcare through computational and statistical methods to understand the genomics and environment architecture of complex diseases, variation in drug/treatment response. This interest is extending in methodologies and developing tools for deconvoluting human genomics diversity to uncover the role of genetic and environmental factors in determining risk and susceptibility of communicable and non-communicable diseases. I develop Bioinformatics methods/tools pertinent to genetic and environmental determinants of susceptibility to complex diseases, drug responses, genome variation, microbial omics, and infectious diseases from both the host and pathogen perspectives to facilitate the transformation of genomics-driven clinical practice.
Our current range of developed Bioinformatics tools from functional genomics, post-Genome-wide Association Studies, disease risk prediction, Gene Ontology semantic similarity can be found at ().
I am actively involved in the development of bioinformatics and Omics Data Science educational courses to offer a unique opportunity in the use of bioinformatics and computational methods to access and harness large complicated high-throughput data and uncover meaningful information that could be used to understand molecular mechanisms and develop novel targeted therapeutics/diagnostic tools.
Bioinformatics PhD July 01 2013
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