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  • Multiple sequence alignment of homologous cytochrome C protein sequences using Jalview viewer.

    Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...

    Learning Objectives
    At 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.
  • blind cave fish
  • A tuco-tuco in South America (photo credit: Jeremy Hsu)

    Furry with a chance of evolution: Exploring genetic drift with tuco-tucos

    Learning Objectives
    • Students will be able to explain how genetic drift leads to allelic changes over generations.
    • Students will be able to demonstrate that sampling error can affect every generation, which can result in random changes in allelic frequency.
    • Students will be able to explore and evaluate the effect of population size on the strength of genetic drift.
    • Students will be able to analyze quantitative data associated with genetic drift.