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Investigating Cell Signaling with Gene Expression DatasetsLearning ObjectivesStudents will be able to:
- Explain the hierarchical organization of signal transduction pathways.
- Explain the role of enzymes in signal propagation and amplification.
- Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
- Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
- Use software to analyze and interpret gene expression data.
- Use an appropriate statistical method for hypotheses testing.
- Produce reports that are written in scientific style.
Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced studentsLearning ObjectivesStudents will:
- Articulate testable hypotheses. (Lab 8, final presentation/paper, in-class exercises)
- Analyze data to determine the level of support for articulated hypotheses. (Labs 4-7, final presentation/paper)
- Identify multiple species of plants in the field quickly and accurately. (Labs 2-3, field trip)
- Measure environmental variables and sample vegetation in the field. (Labs 2-3, field trip)
- Analyze soil samples using a variety of low-tech lab techniques. (Open labs after field trip)
- Use multiple statistical techniques to analyze data for patterns. (Labs 4-8, final presentation/paper)
- Interpret statistical analyses to distinguish between strong and weak interactions in a biological system. (Labs 4-7, final presentation/paper)
- Develop and present a conference-style presentation in a public forum. (Lab 8, final presentation/paper)
- Write a publication-ready research paper communicating findings and displaying data. (Lab 8, final presentation/paper)
A first lesson in mathematical modeling for biologists: RocsLearning Objectives
- Systematically develop a functioning, discrete, single-species model of an exponentially-growing or -declining population.
- Use the model to recommend appropriate action for population management.
- Communicate model output and recommendations to non-expert audiences.
- Generate a collaborative work product that most individuals could not generate on their own, given time and resource constraints.
Using QIIME to Interpret Environmental Microbial Communities in an Upper Level Metagenomics CourseLearning ObjectivesStudents will be able to:
- list and perform the steps of sequence processing and taxonomic inference.
- interpret microbial community diversity from metagenomic sequence datasets.
- compare microbial diversity within and between samples or treatments.