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  • Possible implementations of a short research module

    A Short Laboratory Module to Help Infuse Metacognition during an Introductory Course-based Research Experience

    Learning Objectives
    • Students will be able to evaluate the strengths and weaknesses of data.
    • Students will be able to employ prior knowledge in formulating a biological research question or hypothesis.
    • Students will be able to distinguish a research question from a testable hypothesis.
    • Students will recognize that the following are essential elements in experimental design: identifying gaps in prior knowledge, picking an appropriate approach (ex. experimental tools and controls) for testing a hypothesis, and reproducibility and repeatability.
    • Students will be able to identify appropriate experimental tools, approaches and controls to use in testing a hypothesis.
    • Students will be able to accurately explain why an experimental approach they have selected is a good choice for testing a particular hypothesis.
    • Students will be able to discuss whether experimental outcomes support or fail to support a particular hypothesis, and in the case of the latter, discuss possible reasons why.
  • 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.
  • 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.
  • 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.
  • pClone Red Makes Research Look Easy

    Using Synthetic Biology and pClone Red for Authentic Research on Promoter Function: Genetics (analyzing mutant...

    Learning Objectives
    • Describe how cells can produce proteins at the right time and correct amount. 
    • Diagram a bacterial promoter with −35 and −10 elements and the transcription start site.
    • Describe how mutational analysis can be used to study promoter sequence requirements.
    • Develop a promoter mutation hypothesis and design an experiment to test it.
    • Successfully and safely manipulate DNA and Escherichia coli for ligation and transformation experiments. 
    • Design an experiment to verify a mutated 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.  
  • Summary diagram of the Pipeline CURE. A diagram describing how undergraduates, faculty, and research trainees progress through a sequence of guided research activities that develop student independence.
  • “The outcome of the Central Dogma is not always intuitive” Variation in gene size does not necessarily correlate with variation in protein size. Here, two related genes differ in length due to a deletion mutation that removes four nucleotides. Many students do not predict that the smaller gene, after transcription and translation, would produce a larger protein.

    Predicting and classifying effects of insertion and deletion mutations on protein coding regions

    Learning Objectives
    Students will be able to:
    • accurately predict effects of frameshift mutations in protein coding regions
    • conduct statistical analysis to compare expected and observed values
    • become familiar with accessing and using DNA sequence databases and analysis tools
  • 3D Print Models: A collection of 3D models printed from online repository files.
  • ACTN3 from https://upload.wikimedia.org/wikipedia/commons/3/33/Protein_ACTN3_PDB_1tjt.png

    The ACTN3 Polymorphism: Applications in Genetics and Physiology Teaching Laboratories

    Learning Objectives
    1. Test hypotheses related to the role of ACTN3 in skeletal muscle function.
    2. Explain how polymorphic variants of the ACTN3 gene affect protein structure and function.
    3. List and explain the differences between fast twitch and slow twitch muscle fibers.
    4. List and explain possible roles of the ACTN3 protein in skeletal muscle function.
    5. Find and analyze relevant scientific publications about the relationship between ACTN3 genotype and muscle function.
    6. Formulate hypotheses related to the relationship between ACTN3 genotype and skeletal muscle function.
    7. Design experiments to test hypotheses about the role of ACTN3 in skeletal muscle function.
    8. Statistically analyze experimental results using relevant software.
    9. Present experimental results in writing.
  • 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.