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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.
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.
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.
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.