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Making Workshops Work: Insights from EDAMAME
Author(s) -
Jaclyn Taroni
Publication year - 2019
Publication title -
msystems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.931
H-Index - 39
ISSN - 2379-5077
DOI - 10.1128/msystems.00467-19
Subject(s) - leverage (statistics) , metagenomics , domain (mathematical analysis) , data science , computer science , plan (archaeology) , microbiome , ecology , artificial intelligence , biology , bioinformatics , geography , archaeology , mathematics , mathematical analysis , biochemistry , gene
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.

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