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Adapting bioinformatics curricula for big data
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are ch...
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/PMC4719066/ https://www.ncbi.nlm.nih.gov/pubmed/25829469 http://dx.doi.org/10.1093/bib/bbv018 |
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author | Greene, Anna C. Giffin, Kristine A. Greene, Casey S. Moore, Jason H. |
author_facet | Greene, Anna C. Giffin, Kristine A. Greene, Casey S. Moore, Jason H. |
author_sort | Greene, Anna C. |
collection | PubMed |
description | Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. |
format | Online Article Text |
id | pubmed-4719066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47190662016-01-21 Adapting bioinformatics curricula for big data Greene, Anna C. Giffin, Kristine A. Greene, Casey S. Moore, Jason H. Brief Bioinform Current Progress in Bioinformatics 2016 Papers Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. Oxford University Press 2016-01 2015-03-30 /pmc/articles/PMC4719066/ /pubmed/25829469 http://dx.doi.org/10.1093/bib/bbv018 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 | Current Progress in Bioinformatics 2016 Papers Greene, Anna C. Giffin, Kristine A. Greene, Casey S. Moore, Jason H. Adapting bioinformatics curricula for big data |
title | Adapting bioinformatics curricula for big data |
title_full | Adapting bioinformatics curricula for big data |
title_fullStr | Adapting bioinformatics curricula for big data |
title_full_unstemmed | Adapting bioinformatics curricula for big data |
title_short | Adapting bioinformatics curricula for big data |
title_sort | adapting bioinformatics curricula for big data |
topic | Current Progress in Bioinformatics 2016 Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719066/ https://www.ncbi.nlm.nih.gov/pubmed/25829469 http://dx.doi.org/10.1093/bib/bbv018 |
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