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Bioinformatics

  • DNA Detective: Genotype to Phenotype. A Bioinformatics Workshop for Middle School to College. In this image, students are selecting the mutant Arabidopsis plant defective for the “mystery” gene that they identified and annotated through the DNA Subway Red Line.
  • SNP model by David Eccles (gringer) [GFDL (http://www.gnu.org/copyleft/fdl.html) or CC BY 4.0 (http://creativecommons.org/licenses/by/4.0)], via Wikimedia Commons

    Exploration of the Human Genome by Investigation of Personalized SNPs

    Learning Objectives
    Students 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.
  • Students use plastic Easter eggs and chocolate pieces to simulate the distribution of HIV in T lymphocytes.

    Infectious Chocolate Joy with a Side of Poissonian Statistics: An activity connecting life science students with subtle...

    Learning Objectives
    • Students will define a Poisson distribution.
    • Students will generate a data set on the probability of a T cell being infected with a virus(es).
    • Students will predict the likelihood of one observing the mean value of viruses occurring.
    • Students will evaluate the outcomes of a random process.
    • Students will hypothesize whether a process is Poissonian and design a test for that hypothesis.
    • Students will collect data and create a histogram from their data.
  • DNA barcoding research in first-year biology curriculum

    CURE-all: Large Scale Implementation of Authentic DNA Barcoding Research into First-Year Biology Curriculum

    Learning Objectives
    Students 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
    Week 5-6: Ecology
    • 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
    Week 7-11: Cellular and Molecular Biology
    • 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
    Week 12-13: Bioinformatics
    • 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
  • “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
  • Multiple sequence alignment of homologous cytochrome C protein sequences using Jalview viewer.

    Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...

    Learning Objectives
    At 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.