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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.
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.
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 Close-Up Look at PCRLearning ObjectivesAt the end of this lesson students will be able to...
- Describe the role of a primer in PCR
- Predict sequence and length of PCR product based on primer sequences
- Recognize that primers are incorporated into the final PCR products and explain why
- Identify covalent and hydrogen bonds formed and broken during PCR
- Predict the structure of PCR products after each cycle of the reaction
- Explain why amplification proceeds exponentially
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.
Exploring the March to Mars Using 3D Print ModelsLearning Objectives
- Students will be able to describe the major aspects of the Mars Curiosity Rover missions.
- Students will be able to synthesize information learned from a classroom jigsaw activity on the Mars Curiosity Rover missions.
- Students will be able to work in teams to plan a future manned mission to Mars.
- Students will be able to summarize their reports to the class.
Linking Genotype to Phenotype: The Effect of a Mutation in Gibberellic Acid Production on Plant GerminationLearning ObjectivesStudents will be able to:
- identify when germination occurs.
- score germination in the presence and absence of GA to construct graphs of collated class data of wild-type and mutant specimens.
- identify the genotype of an unknown sample based on the analysis of their graphical data.
- organize data and perform quantitative data analysis.
- explain the importance of GA for plant germination.
- connect the inheritance of a mutation with the observed phenotype.