Making Workshops Work: Insights from EDAMAME
ABSTRACT Microbiology, like many areas of life science research, is increasingly data-intensive. As such, bioinformatics and data science skills have become essential to leverage microbiome sequencing data for discovery. Short intensive courses have sprung up as formal computational training opportu...
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American Society for Microbiology
2019
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oai:doaj.org-article:a3a6acea625a4edd9f9ffffd24f827ee2021-12-02T19:46:18ZMaking Workshops Work: Insights from EDAMAME10.1128/mSystems.00467-192379-5077https://doaj.org/article/a3a6acea625a4edd9f9ffffd24f827ee2019-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00467-19https://doaj.org/toc/2379-5077ABSTRACT Microbiology, like many areas of life science research, is increasingly data-intensive. As such, bioinformatics and data science skills have become essential to leverage microbiome sequencing data for discovery. Short intensive courses have sprung up as formal computational training opportunities at individual institutions fail to meet demands. In this issue, Shade et al. (A. Shade, T. K. Dunivin, J. Choi, T. K. Teal, et al., mSystems 4:e00297-19, 2019, https://doi.org/10.1128/mSystems.00297-19) share their experience and approach in executing the annual, weeklong Explorations in Data Analysis for Metagenomic Advances in Microbial Ecology (EDAMAME) workshop from 2014 to 2018. EDAMAME introduced learners to general scientific computing concepts and domain-specific data analysis approaches. Workshop learners self-reported appreciable gains in understanding and ability. This report on the EDAMAME workshop strategy and lessons learned will help others in the life sciences to plan, execute, and assess short hands-on computing-intensive courses that support research in a particular domain.Jaclyn N. TaroniAmerican Society for MicrobiologyarticleeducationtrainingMicrobiologyQR1-502ENmSystems, Vol 4, Iss 4 (2019) |
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ABSTRACT Microbiology, like many areas of life science research, is increasingly data-intensive. As such, bioinformatics and data science skills have become essential to leverage microbiome sequencing data for discovery. Short intensive courses have sprung up as formal computational training opportunities at individual institutions fail to meet demands. In this issue, Shade et al. (A. Shade, T. K. Dunivin, J. Choi, T. K. Teal, et al., mSystems 4:e00297-19, 2019, https://doi.org/10.1128/mSystems.00297-19) share their experience and approach in executing the annual, weeklong Explorations in Data Analysis for Metagenomic Advances in Microbial Ecology (EDAMAME) workshop from 2014 to 2018. EDAMAME introduced learners to general scientific computing concepts and domain-specific data analysis approaches. Workshop learners self-reported appreciable gains in understanding and ability. This report on the EDAMAME workshop strategy and lessons learned will help others in the life sciences to plan, execute, and assess short hands-on computing-intensive courses that support research in a particular domain. |
format |
article |
author |
Jaclyn N. Taroni |
author_facet |
Jaclyn N. Taroni |
author_sort |
Jaclyn N. Taroni |
title |
Making Workshops Work: Insights from EDAMAME |
title_short |
Making Workshops Work: Insights from EDAMAME |
title_full |
Making Workshops Work: Insights from EDAMAME |
title_fullStr |
Making Workshops Work: Insights from EDAMAME |
title_full_unstemmed |
Making Workshops Work: Insights from EDAMAME |
title_sort |
making workshops work: insights from edamame |
publisher |
American Society for Microbiology |
publishDate |
2019 |
url |
https://doaj.org/article/a3a6acea625a4edd9f9ffffd24f827ee |
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AT jaclynntaroni makingworkshopsworkinsightsfromedamame |
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