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首页> 外文期刊>Briefings in functional genomics >CGAT: a model for immersive personalized training in computational genomics
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CGAT: a model for immersive personalized training in computational genomics

机译:CGAT:用于计算基因组学的沉浸式个性化训练的模型

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摘要

How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics.
机译:在追求高质量和多样化研究的同时,应如何培训下一代基因组科学家? CGAT是计算基因组学分析和培训计划,由英国医学研究理事会于2010年设立,以补充其对下一代测序能力的投资。 CGAT的构想围绕着双重目标:培训未来的基因组生物学和医学领域的领导者,并为英国科学提供分析基因组规模数据集所需的强大能力。在这里,我们概述了CGAT所采用的培训计划,并描述了它与协作研究项目的契合之处,以使科学家们踏上基因组学的独立研究事业之路。

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