You are here
Search found 9 items
- (-) Remove Bioinformatics filter Bioinformatics
- (-) Remove Lab filter Lab
- (-) Remove Ability to use quantitative reasoning filter Ability to use quantitative reasoning
Using Undergraduate Molecular Biology Labs to Discover Targets of miRNAs in HumansLearning Objectives
- Use biological databases to generate and compare lists of predicted miR targets, and obtain the mRNA sequence of their selected candidate gene
- Use bioinformatics tools to design and optimize primer sets for qPCR
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
An Introduction to Eukaryotic Genome Analysis in Non-model Species for Undergraduates: A tutorial from the Genome...Learning ObjectivesAt the end of the activity, students will be able to:
- Explain the steps involved in genome assembly, annotation, and variant detection to other students and instructors.
- Create meaningful visualizations of their data using the integrated genome viewer.
- Use the Linux command line and web-based tools to answer research questions.
- Produce annotated genomes and call variants from raw sequencing reads in non-model species.
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.
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
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.”)
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.
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.