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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.
  • “Quantifying variation in biodiversity” Groundhogs (Marmota monax) with conspicuous variation awaiting measurements.

    Teaching Biodiversity with Museum Specimens in an Inquiry-Based Lab

    Learning Objectives
    Students completing this lab module will:
    • Learn how to appropriately handle and measure museum specimens.
    • Develop the necessary statistical skills to analyze museum specimen data.
    • Become familiar with how to search an online museum database and integrate supplemental data with their own dataset.
    • Strengthen scientific communication skills by presenting research to their peers.
    • Demonstrate ability to investigate scientific questions and address obstacles that occur during data collection and integration.
    • Increase proficiency in managing and using large datasets for scientific research.
    • Make connections between natural history knowledge and morphology of organisms in developing and testing hypotheses.
  • Structure of protein ADA2

    Understanding Protein Domains: A Modular Approach

    Learning Objectives
    • Students will be able to compare protein sequences and identify conserved regions and putative domains.
    • Students will be able to obtain, examine, and compare structural models of protein domains.
    • Students will be able to interpret data on protein interactions (in vitro pull-down and in vitro and in vivo functional assays)
    • Students will be able to propose experiments to test protein interactions.