Brief. Bioinformatics - Best practices in bioinformatics training for life scientists.

Tópicos

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{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

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.

Resumo Limpo

mountain data thrust new landscap modern highthroughput biolog irrevoc chang biomed research creat nearinsati demand train data manag manipul data mine analysi among life scientist clinician environment research common theme need just use gain familiar bioinformat tool resourc also understand under fundament theoret practic concept provid bioinformat train empow life scientist handl analys data effici progress research challeng across globe deliv good train goe beyond tradit lectur resourcecentr demo use interact problemsolv exercis cooper learn substanti enhanc train qualiti learn outcom context articl discuss various pragmat criteria identifi train need learn object select suitabl traine trainer develop maintain train skill evalu train qualiti adher criteria may help guid cours organ trainer path toward bioinformat train excel import also improv train experi life scientist

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