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  • 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.
  • A A student assists Colorado Parks & Wildlife employees spawning greenback cutthroat trout at the Leadville National Fish Hatchery; B greenback cutthroat trout adults in a hatchery raceway; C tissue samples collected by students to be used for genetic analysis (images taken by S. Love Stowell)

    Cutthroat trout in Colorado: A case study connecting evolution and conservation

    Learning Objectives
    Students will be able to:
    • interpret figures such as maps, phylogenies, STRUCTURE plots, and networks for species delimitation
    • identify sources of uncertainty and disagreement in real data sets
    • propose research to address or remedy uncertainty
    • construct an evidence-based argument for the management of a rare taxon
  • Students engaged in building the PCR model

    A Close-Up Look at PCR

    Learning Objectives
    At the end of this lesson students will be able to...
    • Describe the role of a primer in PCR
    • Predict sequence and length of PCR product based on primer sequences
    • Recognize that primers are incorporated into the final PCR products and explain why
    • Identify covalent and hydrogen bonds formed and broken during PCR
    • Predict the structure of PCR products after each cycle of the reaction
    • Explain why amplification proceeds exponentially
  • The MAP Kinase signal transduction pathway

    Cell Signaling Pathways - a Case Study Approach

    Learning Objectives
    • Use knowledge of positive and negative regulation of signaling pathways to predict the outcome of genetic modifications or pharmaceutical manipulation.
    • From phenotypic data, predict whether a mutation is in a coding or a regulatory region of a gene involved in signaling.
    • Use data, combined with knowledge of pathways, to make reasonable predictions about the genetic basis of altered signaling pathways.
    • Interpret and use pathway diagrams.
    • Synthesize information by applying prior knowledge on gene expression when considering congenital syndromes.
  • Simplified Representation of the Global Carbon Cycle,

    Promoting Climate Change Literacy for Non-majors: Implementation of an atmospheric carbon dioxide modeling activity as...

    Learning Objectives
    • Students will be able to manipulate and produce data and graphs.
    • Students will be able to design a simple mathematical model of atmospheric CO2 that can be used to make predictions.
    • Students will be able to conduct simulations, analyze, interpret, and draw conclusions about atmospheric CO2 levels from their own computer generated simulated data.
  • A pair of homologous chromosomes.

    Meiosis: A Play in Three Acts, Starring DNA Sequence

    Learning Objectives
    • Students will be able to identify sister chromatids and homologous chromosomes at different stages of meiosis.
    • Students will be able to identify haploid and diploid cells, whether or not the chromosomes are replicated.
    • Students will be able to explain why homologous chromosomes must pair during meiosis.
    • Students will be able to relate DNA sequence similarity to chromosomal structures.
    • Students will be able to identify crossing over as the key to proper pairing of homologous chromosomes during meiosis.
    • Students will be able to predict the outcomes of meiosis for a particular individual or cell.
  • 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.
  • This is the question when working with pH and pKa. This is original artwork by the author and no copyright is violated.

    Taking the Hassle out of Hasselbalch

    Learning Objectives
    Students will be able to:
    1. Characterize an aqueous environment as acidic or basic.
    2. Explain that pKa is a measure of how easy it is to remove a proton from a molecule.
    3. Predict ionization state of a molecule at a particular pH based on its pKa (qualitative use of the Henderson-Hasselbalch equation).
    4. Calculate the ratio of protonated/unprotonated forms of ionizable groups depending on chemical characteristics and /or environment pH (quantitative use of the Henderson-Hasselbalch equation).
    5. Apply this knowledge in a medical context.
  • How Silly Putty® is like bone

    What do Bone and Silly Putty® have in Common?: A Lesson on Bone Viscoelasticity

    Learning Objectives
    • Students will be able to explain how the anatomical structure of long bones relates to their function.
    • Students will be able to define viscoelasticity, hysteresis, anisotropy, stiffness, strength, ductility, and toughness.
    • Students will be able to identify the elastic and plastic regions of a stress-strain curve. They will be able to correlate each phase of the stress-strain curve with physical changes to bone.
    • Students will be able to predict how a bone would respond to changes in the magnitude of an applied force, and to variations in the speed or angle at which a force is applied.
    • Students will be able to determine the reason(s) why bone injuries occur more frequently during athletic events than during normal everyday use.
  • Students using the Understanding Eukaryotic Genes curriculum to construct a gene model. Students are working as a pair to complete each Module using classroom computers.

    An undergraduate bioinformatics curriculum that teaches eukaryotic gene structure

    Learning Objectives
    Module 1
    • Demonstrate basic skills in using the UCSC Genome Browser to navigate to a genomic region and to control the display settings for different evidence tracks.
    • Explain the relationships among DNA, pre-mRNA, mRNA, and protein.
    Module 2
    • Describe how a primary transcript (pre-mRNA) can be synthesized using a DNA molecule as the template.
    • Explain the importance of the 5' and 3' regions of the gene for initiation and termination of transcription by RNA polymerase II.
    • Identify the beginning and the end of a transcript using the capabilities of the genome browser.
    Module 3
    • Explain how the primary transcript generated by RNA polymerase II is processed to become a mature mRNA, using the sequence signals identified in Module 2.
    • Use the genome browser to analyze the relationships among:
    • pre-mRNA
    • 5' capping
    • 3' polyadenylation
    • splicing
    • mRNA
    Module 4
    • Identify splice donor and acceptor sites that are best supported by RNA-Seq data and TopHat splice junction predictions.
    • Utilize the canonical splice donor and splice acceptor sequences to identify intron-exon boundaries.
    Module 5
    • Determine the codons for specific amino acids and identify reading frames by examining the Base Position track in the genome browser.
    • Assemble exons to maintain the open reading frame (ORF) for a given gene.
    • Define the phases of the splice donor and acceptor sites and describe how they impact the maintenance of the ORF.
    • Identify the start and stop codons of an assembled ORF.
    Module 6
    • Demonstrate how alternative splicing of a gene can lead to different mRNAs.
    • Show how alternative splicing can lead to the production of different polypeptides and result in drastic changes in phenotype.
  • Arabidopsis Seedling

    Linking Genotype to Phenotype: The Effect of a Mutation in Gibberellic Acid Production on Plant Germination

    Learning Objectives
    Students will be able to:
    • identify when germination occurs.
    • score germination in the presence and absence of GA to construct graphs of collated class data of wild-type and mutant specimens.
    • identify the genotype of an unknown sample based on the analysis of their graphical data.
    • organize data and perform quantitative data analysis.
    • explain the importance of GA for plant germination.
    • connect the inheritance of a mutation with the observed phenotype.