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Teaching Microbiome Analysis: From Design to Computation Through Inquiry
In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students d...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658192/ https://www.ncbi.nlm.nih.gov/pubmed/33193120 http://dx.doi.org/10.3389/fmicb.2020.528051 |
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author | Rosen, Gail L. Hammrich, Penny |
author_facet | Rosen, Gail L. Hammrich, Penny |
author_sort | Rosen, Gail L. |
collection | PubMed |
description | In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students developed hypotheses, designed lab experiments, sequenced the DNA from microbiomes, learned basic python/R scripting, became proficient in at least one microbiome analysis software, and were able to analyze data generated from the microbiome experiments. While over 150 students (graduate and undergraduate) were impacted by the development of the series of courses, our assessment was only on undergraduate learning, where 45 students enrolled in at least one of the three courses and 4 students took all three. Students gained skills in bioinformatics through the courses, and several positive comments were received through surveys and private correspondence. Through a summative assessment, general trends show that students became more proficient in comparative genomic techniques and had positive attitudes toward their abilities to bridge biology and bioinformatics. While most students took individual or 2 of the courses, we show that pre- and post-surveys of these individual classes still showed progress toward learning objectives. It is expected that students trained will enter the workforce with skills needed to innovate in the biotechnology, health, and environmental industries. Students are trained to maximize impact and tackle real world problems in biology and medicine with their learned knowledge of data science and machine learning. The course materials for the new microbiome analysis course are available on Github: https://github.com/EESI/Comp_Metagenomics_resources. |
format | Online Article Text |
id | pubmed-7658192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76581922020-11-13 Teaching Microbiome Analysis: From Design to Computation Through Inquiry Rosen, Gail L. Hammrich, Penny Front Microbiol Microbiology In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students developed hypotheses, designed lab experiments, sequenced the DNA from microbiomes, learned basic python/R scripting, became proficient in at least one microbiome analysis software, and were able to analyze data generated from the microbiome experiments. While over 150 students (graduate and undergraduate) were impacted by the development of the series of courses, our assessment was only on undergraduate learning, where 45 students enrolled in at least one of the three courses and 4 students took all three. Students gained skills in bioinformatics through the courses, and several positive comments were received through surveys and private correspondence. Through a summative assessment, general trends show that students became more proficient in comparative genomic techniques and had positive attitudes toward their abilities to bridge biology and bioinformatics. While most students took individual or 2 of the courses, we show that pre- and post-surveys of these individual classes still showed progress toward learning objectives. It is expected that students trained will enter the workforce with skills needed to innovate in the biotechnology, health, and environmental industries. Students are trained to maximize impact and tackle real world problems in biology and medicine with their learned knowledge of data science and machine learning. The course materials for the new microbiome analysis course are available on Github: https://github.com/EESI/Comp_Metagenomics_resources. Frontiers Media S.A. 2020-10-29 /pmc/articles/PMC7658192/ /pubmed/33193120 http://dx.doi.org/10.3389/fmicb.2020.528051 Text en Copyright © 2020 Rosen and Hammrich. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Rosen, Gail L. Hammrich, Penny Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title | Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title_full | Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title_fullStr | Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title_full_unstemmed | Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title_short | Teaching Microbiome Analysis: From Design to Computation Through Inquiry |
title_sort | teaching microbiome analysis: from design to computation through inquiry |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658192/ https://www.ncbi.nlm.nih.gov/pubmed/33193120 http://dx.doi.org/10.3389/fmicb.2020.528051 |
work_keys_str_mv | AT rosengaill teachingmicrobiomeanalysisfromdesigntocomputationthroughinquiry AT hammrichpenny teachingmicrobiomeanalysisfromdesigntocomputationthroughinquiry |