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Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set u...
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Formato: | Texto |
Lenguaje: | English |
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American Society for Cell Biology
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2931669/ https://www.ncbi.nlm.nih.gov/pubmed/20810954 http://dx.doi.org/10.1187/cbe.09-09-0067 |
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author | Tra, Yolande V. Evans, Irene M. |
author_facet | Tra, Yolande V. Evans, Irene M. |
author_sort | Tra, Yolande V. |
collection | PubMed |
description | BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. |
format | Text |
id | pubmed-2931669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | American Society for Cell Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-29316692010-09-02 Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines Tra, Yolande V. Evans, Irene M. CBE Life Sci Educ Essays BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. American Society for Cell Biology 2010 /pmc/articles/PMC2931669/ /pubmed/20810954 http://dx.doi.org/10.1187/cbe.09-09-0067 Text en © 2010 Y. V. Tra and I. M. Evans CBE-Life Sciences Education © 2010 The American Society for Cell Biology under license from the author(s). It is available to the public under Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0). |
spellingShingle | Essays Tra, Yolande V. Evans, Irene M. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title | Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title_full | Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title_fullStr | Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title_full_unstemmed | Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title_short | Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines |
title_sort | enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines |
topic | Essays |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2931669/ https://www.ncbi.nlm.nih.gov/pubmed/20810954 http://dx.doi.org/10.1187/cbe.09-09-0067 |
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