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A CURE-based approach to teaching genomics using mitochondrial genomesLearning Objectives
- Install the appropriate programs such as Putty and WinSCP.
- Navigate NCBI's website including their different BLAST programs (e.g., blastn, tblastx, blastp and blastx)
- Use command-line BLAST to identify mitochondrial contigs within a whole genome assembly
- Filter the desired sequence (using grep) and move the assembled mitochondrial genome onto your own computer (using FTP or SCP)
- Error-correct contigs (bwa mem, samtools tview), connect and circularize organellar contigs (extending from filtered reads)
- Transform assembled sequences into annotated genomes
- Orient to canonical start locations in the mitochondrial genome (cox1)
- Identify the boundaries of all coding components of the mitochondrial genome using BLAST, including: Protein coding genes (BLASTx and tBLASTX), tRNAs (proprietary programs such as tRNAscan), rRNAs (BLASTn, Chlorobox), ORFs (NCBI's ORFFinder)
- Deposit annotation onto genome repository (NCBI)
- Update CV/resume to reflect bioinformatics skills learned in this lesson
Using computational molecular modeling software to demonstrate how DNA mutations cause phenotypesLearning ObjectivesStudents successfully completing this lesson will:
- Practice basic molecular biology laboratory skills such as DNA isolation, PCR, and gel electrophoresis.
- Gather and analyze quantitative and qualitative scientific data and present it in figures.
- Use bioinformatics to analyze DNA sequences and obtain protein sequences for molecular modeling.
- Make and analyze three-dimensional (3-D) protein models using molecular modeling software.
- Write a laboratory report using the collected data to explain how mutations in the DNA cause changes in protein structure/function which lead to mutant phenotypes.
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)
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.
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.
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.
Promoting Climate Change Literacy for Non-majors: Implementation of an atmospheric carbon dioxide modeling activity as...Learning Objectives
- Students will be able to manipulate and produce data and graphs.
- Students will be able to design a simple mathematical model of atmospheric CO2 that can be used to make predictions.
- Students will be able to conduct simulations, analyze, interpret, and draw conclusions about atmospheric CO2 levels from their own computer generated simulated data.
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.
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.
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.
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