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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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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. |
format | Online Article Text |
id | pubmed-4812590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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