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 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.

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REMNet: Online Resources 5.3.19

Video on online resources for studying microbiomes from the Research Experiences in Microbiomes Network

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GSD QUBES Resource Draft (1)

This QUBES module is focused towards AP Environmental studies courses. It includes hypothesis testing, transect sampling, Shannon Diversity Index, and scatter plot and bar graph creation in excel.

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Introduction to Primate Data Exploration and Linear Modeling with R

Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology research students on data management and statistical analysis using authentic data of Cayo Santiago rhesus macaques.

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