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  • Plant ecology students surveying vegetation at Red Hills, CA, spring 2012.  From left to right are G.L, F.D, A.M., and R.P.  Photo used with permission from all students.

    Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced students

    Learning Objectives
    Students will:
    • Articulate testable hypotheses. (Lab 8, final presentation/paper, in-class exercises)
    • Analyze data to determine the level of support for articulated hypotheses. (Labs 4-7, final presentation/paper)
    • Identify multiple species of plants in the field quickly and accurately. (Labs 2-3, field trip)
    • Measure environmental variables and sample vegetation in the field. (Labs 2-3, field trip)
    • Analyze soil samples using a variety of low-tech lab techniques. (Open labs after field trip)
    • Use multiple statistical techniques to analyze data for patterns. (Labs 4-8, final presentation/paper)
    • Interpret statistical analyses to distinguish between strong and weak interactions in a biological system. (Labs 4-7, final presentation/paper)
    • Develop and present a conference-style presentation in a public forum. (Lab 8, final presentation/paper)
    • Write a publication-ready research paper communicating findings and displaying data. (Lab 8, final presentation/paper)
  • Images of students participating in the SIDE activity

    Using a Sequential Interpretation of Data in Envelopes (SIDE) approach to identify a mystery TRP channel

    Learning Objectives
    • Students will be able to analyze data from multiple experimental methodologies to determine the identity of their "mystery" TRP channel.
    • Students will be able to interpret the results of individual experiments and from multiple experiments simultaneously to identify their "mystery" TRP channel.
    • Students will be able to evaluate the advantages and limitations of experimental methodologies presented in this lesson.
  • 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.
  • Format of a typical course meeting
  • Evaluating the Quick Fix: Weight Loss Drugs and Cellular Respiration Image File: QuickFixPrimImage.tiff Sources for images: Balance: Public Domain CCO http://www.pd4pic.com/scales-justice-scale-libra-balance-weighbridge.html Mitochondria: https://thumb7.shutterstock.com/thumb_large/1503584/235472731/stock-vector-mitochondrion-235472731.jpg Pills: https://pixabay.com/static/uploads/photo/2014/07/05/15/16/pills-384846_960_720.jpg

    Evaluating the Quick Fix: Weight Loss Drugs and Cellular Respiration

    Learning Objectives
    • Students will be able to explain how the energy from sugars is transformed into ATP via cellular respiration.
    • Students will be able to predict an outcome if there is a perturbation in the cellular respiration pathway.
    • Students will be able to state and evaluate a hypothesis.
    • Students will be able to interpret data from a graph, and use that data to make inferences about the action of a drug.
  • Example image of dividing cells obtained from the Allen Institute for Cell Science 3D Cell Viewer.

    A virtual laboratory on cell division using a publicly-available image database

    Learning Objectives
    • Students will name and describe the salient features and cellular tasks for each stage of cell division.
    • Students will predict the relative durations of the stages of cell division using prior knowledge and facts from assigned readings.
    • Students will describe the relationship between duration of each stage of cell division and the frequency of cells present in each stage of cell division counted in a random sample of images of pluripotent stem cells.
    • Students will identify the stages of cell division present in research-quality images of human pluripotent stem cells in various stages of cell division.
    • Students will quantify, analyze and summarize data on the prevalence of cells at different stages of cell division in randomly sampled cell populations.
    • Students will use data to reflect on and revise predictions.
  • 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
  • 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.