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Investigating Cell Signaling with Gene Expression Datasets
Modern molecular biology is a data- and computationally-intensive field with few instructional resources for introducing undergraduate students to the requisite skills and techniques for analyzing large data sets. This Lesson helps students: (i) build an understanding of the role of signal transduct...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449260/ https://www.ncbi.nlm.nih.gov/pubmed/32855998 http://dx.doi.org/10.24918/cs.2019.1 |
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author | Wachira, James Hughes-Darden, Cleo Nkwanta, Asamoah |
author_facet | Wachira, James Hughes-Darden, Cleo Nkwanta, Asamoah |
author_sort | Wachira, James |
collection | PubMed |
description | Modern molecular biology is a data- and computationally-intensive field with few instructional resources for introducing undergraduate students to the requisite skills and techniques for analyzing large data sets. This Lesson helps students: (i) build an understanding of the role of signal transduction in the control of gene expression; (ii) improve written scientific communication skills through engagement in literature searches, data analysis, and writing reports; and (iii) develop an awareness of the procedures and protocols for analyzing and making inferences from high-content quantitative molecular biology data. The Lesson is most suited to upper level biology courses because it requires foundational knowledge on cellular organization, protein structure and function, and the tenets of information flow from DNA to proteins. The first step lays the foundation for understanding cell signaling, which can be accomplished through assigned readings and presentations. In subsequent active learning sessions, data analysis is integrated with exercises that provide insight into the structure of scientific papers. The Lesson emphasizes the role of quantitative methods in research and helps students gain experience with functional genomics databases and data analysis, which are important skills for molecular biologists. Assessment is conducted through mini-reports designed to gauge students’ perceptions of the purpose of each step, their awareness of the possible limitations of the methods utilized, and the ability to identify opportunities for further investigation. Summative assessment is conducted through a final report. The modules are suitable for complementing wet-laboratory experiments and can be adapted for different courses that use molecular biology data. |
format | Online Article Text |
id | pubmed-7449260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
record_format | MEDLINE/PubMed |
spelling | pubmed-74492602020-08-26 Investigating Cell Signaling with Gene Expression Datasets Wachira, James Hughes-Darden, Cleo Nkwanta, Asamoah CourseSource Article Modern molecular biology is a data- and computationally-intensive field with few instructional resources for introducing undergraduate students to the requisite skills and techniques for analyzing large data sets. This Lesson helps students: (i) build an understanding of the role of signal transduction in the control of gene expression; (ii) improve written scientific communication skills through engagement in literature searches, data analysis, and writing reports; and (iii) develop an awareness of the procedures and protocols for analyzing and making inferences from high-content quantitative molecular biology data. The Lesson is most suited to upper level biology courses because it requires foundational knowledge on cellular organization, protein structure and function, and the tenets of information flow from DNA to proteins. The first step lays the foundation for understanding cell signaling, which can be accomplished through assigned readings and presentations. In subsequent active learning sessions, data analysis is integrated with exercises that provide insight into the structure of scientific papers. The Lesson emphasizes the role of quantitative methods in research and helps students gain experience with functional genomics databases and data analysis, which are important skills for molecular biologists. Assessment is conducted through mini-reports designed to gauge students’ perceptions of the purpose of each step, their awareness of the possible limitations of the methods utilized, and the ability to identify opportunities for further investigation. Summative assessment is conducted through a final report. The modules are suitable for complementing wet-laboratory experiments and can be adapted for different courses that use molecular biology data. 2019-01-03 2019 /pmc/articles/PMC7449260/ /pubmed/32855998 http://dx.doi.org/10.24918/cs.2019.1 Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. The authors affirm that they either own the copyright to, utilize images under the Creative Commons Attribution 4.0 License, or have received written permission to use the text, figures, tables, artwork, abstract, summaries and supporting materials. |
spellingShingle | Article Wachira, James Hughes-Darden, Cleo Nkwanta, Asamoah Investigating Cell Signaling with Gene Expression Datasets |
title | Investigating Cell Signaling with Gene Expression Datasets |
title_full | Investigating Cell Signaling with Gene Expression Datasets |
title_fullStr | Investigating Cell Signaling with Gene Expression Datasets |
title_full_unstemmed | Investigating Cell Signaling with Gene Expression Datasets |
title_short | Investigating Cell Signaling with Gene Expression Datasets |
title_sort | investigating cell signaling with gene expression datasets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449260/ https://www.ncbi.nlm.nih.gov/pubmed/32855998 http://dx.doi.org/10.24918/cs.2019.1 |
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