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Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high pe...

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Detalles Bibliográficos
Autores principales: Barone, Lindsay, Williams, Jason, Micklos, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654259/
https://www.ncbi.nlm.nih.gov/pubmed/29049281
http://dx.doi.org/10.1371/journal.pcbi.1005755
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author Barone, Lindsay
Williams, Jason
Micklos, David
author_facet Barone, Lindsay
Williams, Jason
Micklos, David
author_sort Barone, Lindsay
collection PubMed
description In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.
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spelling pubmed-56542592017-11-08 Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators Barone, Lindsay Williams, Jason Micklos, David PLoS Comput Biol Education In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology. Public Library of Science 2017-10-19 /pmc/articles/PMC5654259/ /pubmed/29049281 http://dx.doi.org/10.1371/journal.pcbi.1005755 Text en © 2017 Barone et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Education
Barone, Lindsay
Williams, Jason
Micklos, David
Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title_full Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title_fullStr Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title_full_unstemmed Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title_short Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
title_sort unmet needs for analyzing biological big data: a survey of 704 nsf principal investigators
topic Education
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654259/
https://www.ncbi.nlm.nih.gov/pubmed/29049281
http://dx.doi.org/10.1371/journal.pcbi.1005755
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