Bioinformatics mentorship in a resource limited setting

Author:

Jjingo Daudi12ORCID,Mboowa Gerald13ORCID,Sserwadda Ivan13,Kakaire Robert4,Kiberu Davis1,Amujal Marion3,Galiwango Ronald13,Kateete David35,Joloba Moses35,Whalen Christopher C4

Affiliation:

1. The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda

2. Department of Computer Science, College of Computing and Information Sciences, Makerere University, Kampala-Uganda

3. Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda

4. Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA

5. Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala-Uganda

Abstract

Abstract Background The two recent simultaneous developments of high-throughput sequencing and increased computational power have brought bioinformatics to the forefront as an important tool for effective and efficient biomedical research. Consequently, there have been multiple approaches to developing bioinformatics skills. In resource rich environments, it has been possible to develop and implement formal fully accredited graduate degree training programs in bioinformatics. In resource limited settings with a paucity of expert bioinformaticians, infrastructure and financial resources, the task has been approached by delivering short courses on bioinformatics—lasting only a few days to a couple of weeks. Alternatively, courses are offered online, usually over a period of a few months. These approaches are limited by both the lack of sustained in-person trainer–trainee interactions, which is a key part of quality mentorships and short durations which constrain the amount of learning that can be achieved. Methods Here, we pioneered and tested a bioinformatics training/mentorship model that effectively uses the available expertise and computational infrastructure to deliver an in-person hands-on skills training experience. This is done through a few physical lecture hours each week, guided personal coursework over the rest of the week, group discussions and continuous close mentorship and assessment of trainees over a period of 1 year. Results This model has now completed its third iteration at Makerere University and has successfully mentored trainees, who have progressed to a variety of viable career paths. Conclusions One-year (intermediate) skills based in-person bioinformatics training and mentorships are viable, effective and particularly appropriate for resource limited settings.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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