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    Louse Genetics, Genomics, and Gene Function...Oh My!
    In this module, students will be investigating a louse gene with an unknown function to determine if it might be important in the evolution of the louse ecomorphs.
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    Birds and Lice: Reciprocal Natural Selection
    This exercise investigates the form and function of lice and their relationship to their bird host.
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    Louse and Human Coevolution
    This module examines the complicated co-evolution of Lice, Humans, and Great Apes
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    Movement: Nature's Flying Machines (Online)
    Adapted for online learning: In this lab, you will explore the physics of flight, the adaptations that make powered flight possible, and the evolution of powered flight in vertebrates and...
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    Does Organelle Shape Matter? Exploring Cell Shape through the Allen Cell Explorer and High-content Microscopy Datasets
    The morphology and localization of structures inside the cell are often assumed to fit the ideal images found in biology textbooks. This interrupted case study using high-throughput microscopy data...
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    Chi-squared test of independence between two categorical variables
    In this lesson, students will have the opportunity to work through a chi-squared test of independence between two categorical variables.
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    Responses to Climate Change in California Chipmunks: Move, Adapt, or Die
    A series of three modules using data from natural history museum collections to examine responses to climate change in multiple chipmunk species. Elevation and morphological data, beginner skills...
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    Introduction to Genome Annotation
    This exercise is an adaptation of the Annotation Lesson by Rosenwald et al. It introduces the use of bioinformatics tools to extract information from genome databases. It is a basic lesson on...
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    REMNet Tutorial, Excel Part 3: Organizing Your Microbiome Data 5.3.19
    Video on organizing microbiome using Excel from the Research Experiences in Microbiomes Network
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    Teaching introductory bioinformatics with Jupyter notebook-based active learning
    Presentation on teaching introductory bioinformatics with Jupyter notebook-based active learning at the 2019 Great Lakes Bioinformatics Conference
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    Build-a-Phage Lab Manual
    This is a lab manual for phage genome synthesis that includes both Building Block synthesis and Semi-synthetic assembly.
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    Aquatic Nutrient Levels and Climate Change
    This learning module was designed to introduce students to the aquatic nutrients nitrogen and phosphorus, their roles in ecosystem function and nutrient pollution, and what impacts climate change...
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    The p53 Gene and Cancer
    This tutorial describes the structure and function of the p53 protein, how its activity is regulated in cells, and how mutant versions of p53 can lead to cancer.
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    Cystic Fibrosis Mechanism and Treatment
    This animation shows how mutations in an ion channel protein lead to the genetic disease cystic fibrosis. The animation also discusses how research on this protein has been used to develop...
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    Adaptation of Investigating human impacts on stream ecology: locally and nationally
    TIEE Module- How does nutrient pollution impact stream ecosystems locally and nationally?
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    Movement: Nature's Flying Machines
    In this lab, you will explore the physics of flight, the adaptations that make powered flight possible, and the evolution of powered flight in vertebrates and invertebrates.
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    AVIDA exercise on the role of mutation in evolution
    A tested exercise at the college freshmen level using AVIDA-Ed to generate and test a hypothesis about the relationship between mutation rate and the probability of evolving a useful function in...
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    Amylase Copy Number and Diet
    An adapted module from HHMI Spreadsheet Tutorials using amylase data for students to gain data analysis and excel skills
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    Spider Silk: Stress-Strain Curves and Young's Modulus
    This module introduces the stress-strain curve in the context of understanding materials' mechanical behavior. It is intended for an introductory biology audience.
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    Exploring the functionality of R
    Students work with example data to generate a length-weight plot and use lm() to obtain regression coefficients. Base plot functions are used to plot both the data and the regression line.
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