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CGAT: a model for immersive personalized training in computational genomics

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 se...

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Detalles Bibliográficos
Autores principales: Sims, David, Ponting, Chris P., Heger, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4812590/
https://www.ncbi.nlm.nih.gov/pubmed/25981124
http://dx.doi.org/10.1093/bfgp/elv021
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author Sims, David
Ponting, Chris P.
Heger, Andreas
author_facet Sims, David
Ponting, Chris P.
Heger, Andreas
author_sort Sims, David
collection PubMed
description 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.
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spelling pubmed-48125902016-04-04 CGAT: a model for immersive personalized training in computational genomics Sims, David Ponting, Chris P. Heger, Andreas Brief Funct Genomics Papers 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. Oxford University Press 2016-01 2015-05-16 /pmc/articles/PMC4812590/ /pubmed/25981124 http://dx.doi.org/10.1093/bfgp/elv021 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Papers
Sims, David
Ponting, Chris P.
Heger, Andreas
CGAT: a model for immersive personalized training in computational genomics
title CGAT: a model for immersive personalized training in computational genomics
title_full CGAT: a model for immersive personalized training in computational genomics
title_fullStr CGAT: a model for immersive personalized training in computational genomics
title_full_unstemmed CGAT: a model for immersive personalized training in computational genomics
title_short CGAT: a model for immersive personalized training in computational genomics
title_sort cgat: a model for immersive personalized training in computational genomics
topic Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4812590/
https://www.ncbi.nlm.nih.gov/pubmed/25981124
http://dx.doi.org/10.1093/bfgp/elv021
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