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Research article - Peer-reviewed, 2013

Best practices in bioinformatics training for life scientists

Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik; Brazas, Michelle D.; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; Fernandes, P.; van Gelder, Cecilia; Jacob, Joachim; Jimenez, Rafael C.; Loveland, Jane; Moran, Frederico; Mulder, Nicola; Nyrönen, Tommi; Rother, Kristian; Schneider, Maria Victoria; Attwood, Teresa K.


The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.


bioinformatics; training; bioinformatics courses; training life scientists; train the trainers

Published in

Briefings in Bioinformatics
2013, Volume: 14, number: 5, pages: 528-537

    Sustainable Development Goals

    SDG4 Quality education

    UKÄ Subject classification

    Genetics and Breeding
    Bioinformatics (Computational Biology)

    Publication identifier


    Permanent link to this page (URI)