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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.
Predicting and classifying effects of insertion and deletion mutations on protein coding regionsLearning ObjectivesStudents will be able to:
- accurately predict effects of frameshift mutations in protein coding regions
- conduct statistical analysis to compare expected and observed values
- become familiar with accessing and using DNA sequence databases and analysis tools
Teaching the Biological Relevance of Chemical Kinetics Using Cold-Blooded Animal BiologyLearning ObjectivesStudents will be able to:
- Predict the effect of reaction temperature on the rate of a chemical reaction
- Interpret a graph plotted between rate of a chemical reaction and temperature
- Discuss chemical kinetics utilizing case studies of cold-blooded animals
The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cupsLearning ObjectivesStudents will able to:
- compare and contrast spatial and temporal summation in terms of the number of presynaptic events and the timing of these events
- predict the relative contribution to reaching threshold and firing an action potential as a function of distance from the axon hillock
- predict how the frequency of incoming presynaptic action potentials effects the success of temporal summation of resultant postsynaptic potentials