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  • 3D Print Model of the Mars Curiosity Rover, printed from NASA 3D Resources (https://nasa3d.arc.nasa.gov/detail/mars-rover-curiosity)

    Exploring the March to Mars Using 3D Print Models

    Learning Objectives
    • Students will be able to describe the major aspects of the Mars Curiosity Rover missions.
    • Students will be able to synthesize information learned from a classroom jigsaw activity on the Mars Curiosity Rover missions.
    • Students will be able to work in teams to plan a future manned mission to Mars.
    • Students will be able to summarize their reports to the class.
  • Mechanisms regulating the lac operon system

    Discovering Prokaryotic Gene Regulation by Building and Investigating a Computational Model of the lac Operon

    Learning Objectives
    Students will be able to:
    • model how the components of the lac operon contribute to gene regulation and expression.
    • generate and test predictions using computational modeling and simulations.
    • interpret and record graphs displaying simulation results.
    • relate simulation results to cellular events.
    • describe how changes in environmental glucose and lactose levels impact regulation of the lac operon.
    • predict, test, and explain how mutations in specific elements in the lac operon affect their protein product and other elements within the operon.
  • Fully annotated mitochondrial genome of a lichenized fungal species (Cladonia subtenuis).  This represents a visual representation of the final project result of the lesson plan. Students will submit their annotation to NCBI (GenBank) and upon acceptance of their annotation, they typically add this publicly available resource into their resume.

    A CURE-based approach to teaching genomics using mitochondrial genomes

    Learning Objectives
    • Install the appropriate programs such as Putty and WinSCP.
    • Navigate NCBI's website including their different BLAST programs (e.g., blastn, tblastx, blastp and blastx)
    • Use command-line BLAST to identify mitochondrial contigs within a whole genome assembly
    • Filter the desired sequence (using grep) and move the assembled mitochondrial genome onto your own computer (using FTP or SCP)
    • Error-correct contigs (bwa mem, samtools tview), connect and circularize organellar contigs (extending from filtered reads)
    • Transform assembled sequences into annotated genomes
    • Orient to canonical start locations in the mitochondrial genome (cox1)
    • Identify the boundaries of all coding components of the mitochondrial genome using BLAST, including: Protein coding genes (BLASTx and tBLASTX), tRNAs (proprietary programs such as tRNAscan), rRNAs (BLASTn, Chlorobox), ORFs (NCBI's ORFFinder)
    • Deposit annotation onto genome repository (NCBI)
    • Update CV/resume to reflect bioinformatics skills learned in this lesson
  • MA plot of RNA-seq data. An MA plot is a visual summary of gene expression data which identifies genes showing differential expression between two treatments.

    Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using Galaxy

    Learning Objectives
    • Students will locate and download high-throughput sequence data and genome annotation files from publically available data repositories.
    • Students will use Galaxy to create an automated computational workflow that performs sequence quality assessment, trimming, and mapping of RNA-seq data.
    • Students will analyze and interpret the outputs of RNA-seq analysis programs.
    • Students will identify a group of genes that is differentially expressed between treatment and control samples, and interpret the biological significance of this list of differentially expressed genes.
  • Modeling the Research Process: Authentic human physiology research in a large non-majors course

    Learning Objectives
    Students will be able to:
    • Read current scientific literature
    • Formulate testable hypotheses
    • Design an experimental procedure to test their hypothesis
    • Make scientific observations
    • Analyze and interpret data
    • Communicate results visually and orally
  • “Phenology of a Dawn Redwood” – Images collected by students for this lesson pieced together illustrating a Metasequoia glyptostroboides changing color and dropping its leaves in the fall of 2017 on Michigan State University campus.

    Quantifying and Visualizing Campus Tree Phenology

    Learning Objectives
    The Learning Objectives of this lesson span across the entire semester.
    • Observe and collect information on phenological changes in local trees.
    • Become familiar with a database and how to work with large datasets.
    • Analyze and visualize data from the database to test their hypotheses and questions.
    • Develop a research proposal including empirically-driven questions and hypotheses.
    • Synthesize the results of their analysis in the context of plant biodiversity and local environmental conditions.
  • Using Place-Based Economically Relevant Organisms to Improve Student Understanding of the Roles of Carbon Dioxide,...

    Learning Objectives
    At the end of this lesson, students will be able to:
    • Describe the roles of light energy and carbon dioxide in photosynthetic organisms.
    • Identify the effect of nutrients on the growth of photosynthetic organisms.
    • Describe global cycles in atmospheric carbon dioxide levels and how they relate to photosynthetic organisms.
  • The Roc is a mythical giant bird of prey, first conceived during the Islamic Golden Age (~8th to 13th centuries CE), popularized in folk tales gathered in One Thousand One Nights. Rocs figured prominently in tales of Sinbad the Sailor. In this 1898 illustration by René Bull, the Roc is harassing two of Sinbad’s small fleet of ships. Illustration by René Bull is licensed under CC BY 2.0. (Source: https://en.wikipedia.org/wiki/Roc_(mythology)#mediaviewer/File:Rocweb.jpg)

    A first lesson in mathematical modeling for biologists: Rocs

    Learning Objectives
    • Systematically develop a functioning, discrete, single-species model of an exponentially-growing or -declining population.
    • Use the model to recommend appropriate action for population management.
    • Communicate model output and recommendations to non-expert audiences.
    • Generate a collaborative work product that most individuals could not generate on their own, given time and resource constraints.
  • Simplified Representation of the Global Carbon Cycle, https://earthobservatory.nasa.gov/Features/CarbonCycle/images/carbon_cycle.jpg

    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.
     
  • 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
  • Students preforming the leaky neuron activity.

    The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cups

    Learning Objectives
    Students will able to:
    • compare and contrast spatial and temporal summation in terms of the number of presynaptic events and the timing of these events
    • predict the relative contribution to reaching threshold and firing an action potential as a function of distance from the axon hillock
    • predict how the frequency of incoming presynaptic action potentials effects the success of temporal summation of resultant postsynaptic potentials
  • The mechanisms regulating the trp operon system.

    Discovering Prokaryotic Gene Regulation with Simulations of the trp Operon

    Learning Objectives
    Students will be able to:
    • Perturb and interpret simulations of the trp operon.
    • Define how simulation results relate to cellular events.
    • Describe the biological role of the trp operon.
    • Describe cellular mechanisms regulating the trp operon.
    • Explain mechanistically how changes in the extracellular environment affect the trp operon.
    • Define the impact of mutations on trp operon expression and regulation.
  • Using the Cell Engineer/Detective Approach to Explore Cell Structure and Function

    Learning Objectives
    Students will be able to:
    • Identify the major cell organelles
    • List the major functions of the organelles
    • Predict how changes in organelle/cell structure could alter cellular function
    • Explain how overall cellular function is dependent upon organelles/cell structure
    • Relate cell structure to everyday contexts
  • Students use plastic Easter eggs and chocolate pieces to simulate the distribution of HIV in T lymphocytes.

    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.
  • 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.
  • 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.
  • 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
  • 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.
  • Building a Model of Tumorigenesis: A small group activity for a cancer biology/cell biology course

    Learning Objectives
    At the end of the activity, students will be able to:
    • Analyze data from a retrospective clinical study uncovering genetic alterations in colorectal cancer.
    • Draw conclusions about human tumorigenesis using data from a retrospective clinical study.
    • Present scientific data in an appropriate and accurate way.
    • Discuss why modeling is an important practice of science.
    • Create a simple model of the genetic changes associated with a particular human cancer.
  • An active-learning lesson that targets student understanding of population growth in ecology

    Learning Objectives
    Students will be able to:
    • Calculate and compare population density and abundance.
    • Identify whether a growth curve describes exponential, linear, and/or logistic growth.
    • Describe and calculate a population's growth rate using linear, exponential, and logistic models.
    • Explain the influence of carrying capacity and population density on growth rate.
  • Using phylogenetics to make inferences about historical biogeographic patterns of evolution.

    Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeography

    Learning Objectives
    Students will be able to:
    • Estimate phylogenetic trees using diverse data types and phylogenetic models.
    • Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
    • Use selected computer programs for phylogenetic analysis.
    • Use bootstrapping to assess the statistical support for a phylogeny.
    • Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
  • 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.
  • Abelson kinase signaling network. The image shows many connections between genes and illustrates that signaling molecules and pathways function within networks. It emphasizes the indispensability of computational tools in understanding the molecular functioning of cells. The image was generated with Cytoscape from publicly accessible protein-protein interactions databases.

    Investigating Cell Signaling with Gene Expression Datasets

    Learning Objectives
    Students will be able to:
    • Explain the hierarchical organization of signal transduction pathways.
    • Explain the role of enzymes in signal propagation and amplification.
    • Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
    • Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
    • Use software to analyze and interpret gene expression data.
    • Use an appropriate statistical method for hypotheses testing.
    • Produce reports that are written in scientific style.
  • A crossbill feeds on a pinecone

    Coevolution or not? Crossbills, squirrels and pinecones

    Learning Objectives
    1. Define coevolution.
    2. Identify types of evidence that would help determine whether two species are currently in a coevolutionary relationship.
    3. Interpret graphs.
    4. Evaluate evidence about whether two species are coevolving and use evidence to make a scientific argument.
    5. Describe what evidence of a coevolutionary relationship might look like.
    6. Distinguish between coadaptation and coevolution.
  • The mechanisms regulating the cellular respiration system.

    Discovering Cellular Respiration with Computational Modeling and Simulations

    Learning Objectives
    Students will be able to:
    • Describe how changes in cellular homeostasis affect metabolic intermediates.
    • Perturb and interpret a simulation of cellular respiration.
    • Describe cellular mechanisms regulating cellular respiration.
    • Describe how glucose, oxygen, and coenzymes affect cellular respiration.
    • Describe the interconnectedness of cellular respiration.
    • Identify and describe the inputs and outputs of cellular respiration, glycolysis, pyruvate processing, citric acid cycle, and the electron transport chain.
    • Describe how different energy sources are used in cellular respiration.
    • Trace carbon through cellular respiration from glucose to carbon dioxide.