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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)
Modeling the Research Process: Authentic human physiology research in a large non-majors courseLearning ObjectivesStudents will be able to:
- Read current scientific literature
- Formulate testable hypotheses
- Design an experimental procedure to test their hypothesis
- Make scientific observations
- Analyze and interpret data
- Communicate results visually and orally
Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...Learning ObjectivesAt the end of this lesson, students will be able to:
- Define similarity in a non-biological and biological sense when provided with two strings of letters.
- Quantify the similarity between two gene/protein sequences.
- Explain how a substitution matrix is used to quantify similarity.
- Calculate amino acid similarity scores using a scoring matrix.
- Demonstrate how to access genomic data (e.g., from NCBI nucleotide and protein databases).
- Demonstrate how to use bioinformatics tools to analyze genomic data (e.g., BLASTP), explain a simplified BLAST search algorithm including how similarity is used to perform a BLAST search, and how to evaluate the results of a BLAST search.
- Create a nearest-neighbor distance matrix.
- Create a multiple sequence alignment using a nearest-neighbor distance matrix and a phylogram based on similarity of amino acid sequences.
- Use appropriate bioinformatics sequence alignment tools to investigate a biological question.
Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeographyLearning ObjectivesStudents will be able to:
- Estimate phylogenetic trees using diverse data types and phylogenetic models.
- Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
- Use selected computer programs for phylogenetic analysis.
- Use bootstrapping to assess the statistical support for a phylogeny.
- Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
Discovering Cellular Respiration with Computational Modeling and SimulationsLearning ObjectivesStudents will be able to:
- Describe how changes in cellular homeostasis affect metabolic intermediates.
- Perturb and interpret a simulation of cellular respiration.
- Describe cellular mechanisms regulating cellular respiration.
- Describe how glucose, oxygen, and coenzymes affect cellular respiration.
- Describe the interconnectedness of cellular respiration.
- Identify and describe the inputs and outputs of cellular respiration, glycolysis, pyruvate processing, citric acid cycle, and the electron transport chain.
- Describe how different energy sources are used in cellular respiration.
- Trace carbon through cellular respiration from glucose to carbon dioxide.
Discovering Prokaryotic Gene Regulation with Simulations of the trp OperonLearning ObjectivesStudents will be able to:
- Perturb and interpret simulations of the trp operon.
- Define how simulation results relate to cellular events.
- Describe the biological role of the trp operon.
- Describe cellular mechanisms regulating the trp operon.
- Explain mechanistically how changes in the extracellular environment affect the trp operon.
- Define the impact of mutations on trp operon expression and regulation.
Discovering Prokaryotic Gene Regulation by Building and Investigating a Computational Model of the lac OperonLearning ObjectivesStudents will be able to:
- model how the components of the lac operon contribute to gene regulation and expression.
- generate and test predictions using computational modeling and simulations.
- interpret and record graphs displaying simulation results.
- relate simulation results to cellular events.
- describe how changes in environmental glucose and lactose levels impact regulation of the lac operon.
- predict, test, and explain how mutations in specific elements in the lac operon affect their protein product and other elements within the operon.