You are here
Search found 10 items
- (-) Remove Lab filter Lab
- (-) Remove One class period filter One class period
- (-) Remove Ability to use quantitative reasoning filter Ability to use quantitative reasoning
Exploration of the Human Genome by Investigation of Personalized SNPsLearning ObjectivesStudents successfully completing this lesson will be able to:
- Effectively use the bioinformatics databases (SNPedia, the UCSC Genome Browser, and NCBI) to explore SNPs of interest within the human genome.
- Identify three health-related SNPs of personal interest and use the UCSC Genome Browser to define their precise chromosomal locations and determine whether they lie within a gene or are intergenic.
- Establish a list of all genome-wide association studies correlated with a particular health-related SNP.
- Predict which model organism would be most appropriate for conducting further research on a human disease.
Learning to Pipet Correctly by Pipetting Incorrectly?Learning Objectives
- Students will be able to use analytical balances and micropipettes.
- Students will be able to calculate averages and standard deviations.
- Students will be able to use t-tests to compare two independent samples.
- Students will be able to justify accepting or rejecting a null hypothesis based on an interpretation of p-values.
- Students will learn to use spreadsheet software such as Microsoft Excel and/or Google Sheets
- Students will be able to explain how pipetting incorrectly leads to errors.
Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active TeachingLearning Objectives
- From raw RNAseq data, run a basic analysis culminating in a list of differentially expressed genes.
- Explain and evaluate statistical tests in RNAseq data. Specifically, given the output of a particular test, students should be able to interpret and explain the result.
- Use the Linux command line to complete specified objectives in an RNAseq workflow.
- Generate meaningful visualizations of results from new data in R.
- (In addition, each chapter of this lesson plan contains more specific learning objectives, such as “Students will demonstrate their ability to map reads to a reference.”)
Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...Learning ObjectivesStudents 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 flexible, multi-week approach to plant biology - How will plants respond to higher levels of CO2?Learning ObjectivesStudents will be able to:
- Apply findings from each week's lesson to make predictions and informed hypotheses about the next week's lesson.
- Keep a detailed laboratory notebook.
- Write and peer-edit the sections of a scientific paper, and collaboratively write an entire lab report in the form of a scientific research paper.
- Search for, find, and read scientific research papers.
- Work together as a team to conduct experiments.
- Connect findings and ideas from each week's lesson to get a broader understanding of how plants will respond to higher levels of CO2 (e.g., stomatal density, photosynthetic/respiratory rates, foliar protein concentrations, growth, and resource allocation).
The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cupsLearning ObjectivesStudents 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