Skip to main content

You are here

Filters

Introductory Biology

  • Image from http://www.epa.gov/airdata/ad_maps.html

    Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issues

    Learning Objectives
    Students 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.
  • pClone Red Makes Research Look Easy

    Using Synthetic Biology and pClone Red for Authentic Research on Promoter Function: Introductory Biology (identifying...

    Learning Objectives
    • Describe how cells can produce proteins at the right time and correct amount.
    • Diagram how a repressor works to reduce transcription.
    • Diagram how an activator works to increase transcription.
    • Identify a new promoter from literature and design a method to clone it and test its function.
    • Successfully and safely manipulate DNA and Escherichia coli for ligation and transformation experiments.
    • Design an experiment to verify a new promoter has been cloned into a destination vector.
    • Design an experiment to measure the strength of a promoter.
    • Analyze data showing reporter protein produced and use the data to assess promoter strength.
    • Define type IIs restriction enzymes.
    • Distinguish between type II and type IIs restriction enzymes.
    • Explain how Golden Gate Assembly (GGA) works.
    • Measure the relative strength of a promoter compared to a standard promoter.
  • Adult female Daphnia dentifera. Daphnia spp. make a great study system due to their transparent body and their ease of upkeep in a lab.

    Dynamic Daphnia: An inquiry-based research experience in ecology that teaches the scientific process to first-year...

    Learning Objectives
    Students will be able to:
    • Construct written predictions about 1 factor experiments.
    • Interpret simple (2 variables) figures.
    • Construct simple (2 variables) figures from data.
    • Design simple 1 factor experiments with appropriate controls.
    • Demonstrate proper use of standard laboratory items, including a two-stop pipette, stereomicroscope, and laboratory notebook.
    • Calculate means and standard deviations.
    • Given some scaffolding (instructions), select the correct statistical test for a data set, be able to run a t-test, ANOVA, chi-squared test, and linear regression in Microsoft Excel, and be able to correctly interpret their results.
    • Construct and present a scientific poster.
  • 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.
  • Human karyotype

    Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...

    Learning Objectives
    Students 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
  • A three-dimensional model of methionine is superimposed on a phase contrast micrograph of Saccharomyces cerevisiae from a log phase culture.

    Follow the Sulfur: Using Yeast Mutants to Study a Metabolic Pathway

    Learning Objectives
    At the end of this lesson, students will be able to:
    • use spot plating techniques to compare the growth of yeast strains on solid culture media.
    • predict the ability of specific met deletion strains to grow on media containing various sulfur sources.
    • predict how mutations in specific genes will affect the concentrations of metabolites in the pathways involved in methionine biosynthesis.
  • Set Up Fly Traps: The photo is of the fly traps after being set up for the experiment

    Gotcha! Which fly trap is the best? An introduction to experimental data collection and analysis

    Learning Objectives
    Students will:
    • design and execute an experiment
    • collect, organize, and summarize data
    • analyze and interpret data and make inferences