Via, Allegra3; Blicher, Thomas5; Bongcam-Rudloff, Erik3; Brazas, Michelle D3; Brooksbank, Cath3; Budd, Aidan3; De Las Rivas, Javier3; Dreyer, Jacqueline3; Fernandes, Pedro L3; van Gelder, Celia3; Jacob, Joachim3; Jimenez, Rafael C3; Loveland, Jane3; Moran, Federico3; Mulder, Nicola3; Nyrönen, Tommi3; Rother, Kristian3; Schneider, Maria Victoria3; Attwood, Teresa K3
1 Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet2 Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet3 unknown4 Protein Production and Characterization Platform, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet5 Protein Production and Characterization Platform, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet
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.
Briefings in Bioinformatics, 2013, Vol 14, Issue 5, p. 528-37