Bioinformatics mentorship in a resource limited setting. Issue 1 (30th September 2021)

• Record Type: Journal Article
• Authors: Jjingo, Daudi; Mboowa, Gerald; Sserwadda, Ivan; Kakaire, Robert; Kiberu, Davis; Amujal, Marion; Galiwango, Ronald; Kateete, David; Joloba, Moses; Whalen, Christopher C
• Is Part Of: Briefings in bioinformatics. Volume 23:Issue 1(2022)
• Publication Date: 2021-09-30
• Subjects: bioinformatics -- education -- computational biology -- mentorship -- training -- intermediate; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbab399
• Languages: English
• ISSNs: 1467-5463

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.