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- (-) Remove Introductory Biology filter Introductory Biology
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- (-) Remove Foundational: factual knowledge & comprehension filter Foundational: factual knowledge & comprehension
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CURE-all: Large Scale Implementation of Authentic DNA Barcoding Research into First-Year Biology CurriculumLearning ObjectivesStudents will be able to: Week 1-4: Fundamentals of Science and Biology
- List the major processes involved in scientific discovery
- List the different types of scientific studies and which types can establish causation
- Design experiments with appropriate controls
- Create and evaluate phylogenetic trees
- Define taxonomy and phylogeny and explain their relationship to each other
- Explain DNA sequence divergence and how it applies to evolutionary relationships and DNA barcoding
- Define and measure biodiversity and explain its importance
- Catalog organisms using the morphospecies concept
- Geographically map organisms using smartphones and an online mapping program
- Calculate metrics of species diversity using spreadsheet software
- Use spreadsheet software to quantify and graph biodiversity at forest edges vs. interiors
- Write a formal lab report
- Extract, amplify, visualize and sequence DNA using standard molecular techniques (PCR, gel electrophoresis, Sanger sequencing)
- Explain how DNA extraction, PCR, gel electrophoresis, and Sanger sequencing work at the molecular level
- Trim and assemble raw DNA sequence data
- Taxonomically identify DNA sequences isolated from unknown organisms using BLAST
- Visualize sequence data relationships using sequence alignments and gene-based phylogenetic trees
- Map and report data in a publicly available online database
- Share data in a formal scientific poster
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
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.