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Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...Learning ObjectivesStudents successfully completing this lesson will:
- Practice navigating an online bioinformatics resource and identify evidence relevant to solving investigation questions
- Contrast the array of genes expected on homologous autosomal chromosomes pairs with the array of genes expected on sex chromosome pairs
- Use bioinformatics evidence to defend the definition of homologous chromosomes
- Define chromosomal sex and defend the definition using experimental data
- Investigate the genetic basis of human chromosomal sex determination
- Identify at least two genetic mutations can lead to sex reversal
Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issuesLearning ObjectivesStudents will be able to:
- Describe various parameters of air quality that can negatively impact human health, list priority air pollutants, and interpret the EPA Air Quality Index as it relates to human health.
- Identify an air quality problem that varies on spatial and/or temporal scales that can be addressed using publicly available U.S. EPA air data.
- Collect appropriate U.S. EPA Airdata information needed to answer that/those questions, using the U.S. EPA Airdata website data mining tools.
- Analyze the data as needed to address or answer their question(s).
- Interpret data and draw conclusions regarding air quality levels and/or impacts on human and public health.
- Communicate results in the form of a scientific paper.
Understanding Protein Domains: A Modular ApproachLearning 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.
Infectious Chocolate Joy with a Side of Poissonian Statistics: An activity connecting life science students with subtle...Learning Objectives
- Students will define a Poisson distribution.
- Students will generate a data set on the probability of a T cell being infected with a virus(es).
- Students will predict the likelihood of one observing the mean value of viruses occurring.
- Students will evaluate the outcomes of a random process.
- Students will hypothesize whether a process is Poissonian and design a test for that hypothesis.
- Students will collect data and create a histogram from their data.