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Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced studentsLearning ObjectivesStudents 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)
Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using GalaxyLearning 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.
Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...Learning ObjectivesAt 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.
Using QIIME to Interpret Environmental Microbial Communities in an Upper Level Metagenomics CourseLearning ObjectivesStudents will be able to:
- list and perform the steps of sequence processing and taxonomic inference.
- interpret microbial community diversity from metagenomic sequence datasets.
- compare microbial diversity within and between samples or treatments.
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 first lesson in mathematical modeling for biologists: RocsLearning 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.