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    Best practices in bioinformatics training for life scientists

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    Author
    Via, A; Blicher, T; Bongcam-Rudloff, E; Brazas, MD; Brooksbank, C; Budd, A; De Las Rivas, J; Dreyer, J; Fernandes, PL; van Gelder, C; ...
    Date
    2013-09-01
    Source Title
    Briefings in Bioinformatics
    Publisher
    OXFORD UNIV PRESS
    University of Melbourne Author/s
    Schneider, Maria Victoria
    Affiliation
    Medicine Dentistry & Health Sciences
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Via, A., Blicher, T., Bongcam-Rudloff, E., Brazas, M. D., Brooksbank, C., Budd, A., De Las Rivas, J., Dreyer, J., Fernandes, P. L., van Gelder, C., Jacob, J., Jimenez, R. C., Loveland, J., Moran, F., Mulder, N., Nyroenen, T., Rother, K., Schneider, M. V. & Attwood, T. K. (2013). Best practices in bioinformatics training for life scientists. BRIEFINGS IN BIOINFORMATICS, 14 (5), pp.528-537. https://doi.org/10.1093/bib/bbt043.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/259295
    DOI
    10.1093/bib/bbt043
    Abstract
    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.

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