Dr Segun Fatumo
of Genetic Epidemiology & Bioinformatics
I was originally trained as a Computer Scientist with current research experience in Genetic epidemiology and Bioinformatics. I work primarily in Uganda and the United Kingdom, dividing my time between the two. As a Project Leader/Senior Scientist at the MRC/UVRI Uganda, I am responsible for leading large-scale analyses of complex datasets for phenotype and genotype data of the current genomics in Africa. I am also actively involved in capacity building in Africa. I have teaching and/or supervision engagement with the University of Sciences, Techniques and Technologies of Bamako and Covenant University, Nigeria where I am a Visiting Faculty. I also maintain close research collaboration with the H3Africa Bioinformatics Network especially Abuja node Nigeria.
My research largely focuses on the genetic impact of non-communicable diseases in Africa. I am particularly interested in understanding the impact of genetic variation of a range of cardio-metabolic traits in Sub-Sahara Africa.
I received postdoctoral training in genetic epidemiology at the University of Cambridge and Wellcome Trust Sanger Institute and a postdoctoral fellowship in Bioinformatics at the University of Georgia, Athens, USA. Prior to that, I had postgraduate training in applied Bioinformatics at the University of Cologne, Germany and Ph.D. in Computer Science (Bioinformatics specialization) from Covenant University, Nigeria. During my Ph.D., I developed a model which identified twenty-two (22) potential novel drug targets against malaria, some of which have been tested and validated experimentally.
I am the current President of the Nigerian Bioinformatics and Genomics Network and vice-president of the African Society for Bioinformatics and Computational Biology (ASBCB) and where I play a prominent role in the development of bioinformatics and genomics in Africa.
My work largely centres on the genetic basis of cardiometabolic traits and diseases, particularly lipid metabolism, coronary artery and infectious disease, and the use of genetic tools for causal inference.