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  • Using phylogenetics to make inferences about historical biogeographic patterns of evolution.

    Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeography

    Learning Objectives
    Students will be able to:
    • Estimate phylogenetic trees using diverse data types and phylogenetic models.
    • Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
    • Use selected computer programs for phylogenetic analysis.
    • Use bootstrapping to assess the statistical support for a phylogeny.
    • Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
  • Playon Words Title Screen

    Using Gamification to Teach Undergraduate Students about Scientific Writing

    Learning Objectives
    Topics within Playon Words are grouped into “mini-games.” The Learning Objectives for each mini-game are as follows: Sentence Sensei
    • Identify the best sentence variant from a list of options
    • Identify and eliminate needless words
    • Identify where and when to use different types of punctuation marks
    • Identify and correct common grammar mistakes
    Organization Optimizer
    • Organize sentences in a logical order
    • Describe the components of different sections of a scientific paper
    • Identify the section of a scientific paper where a given sentence belongs
    • Eliminate sentences which do not belong in a given writing sample
    Science Officer Training
    • Classify statements as scientific or non-scientific
    • Identify which statements support a particular hypothesis or position
    • Classify provided sentences (e.g. hypotheses vs. predictions, problems vs. experiments, results vs. discussion)
    Reference Referee
    • Compare and contrast different types (e.g. primary literature, review articles, popular literature etc.) and sources (PubMed, Web of Science, Google Scholar etc.) of scientific information
    • Identify locations in texts where citations are needed
    • Identify citations and/or references that are incorrect or missing key information
    • Identify information that does not belong in the reference list (e.g. vendor information)
  • 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.
  • Abelson kinase signaling network. The image shows many connections between genes and illustrates that signaling molecules and pathways function within networks. It emphasizes the indispensability of computational tools in understanding the molecular functioning of cells. The image was generated with Cytoscape from publicly accessible protein-protein interactions databases.

    Investigating Cell Signaling with Gene Expression Datasets

    Learning Objectives
    Students will be able to:
    • Explain the hierarchical organization of signal transduction pathways.
    • Explain the role of enzymes in signal propagation and amplification.
    • Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
    • Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
    • Use software to analyze and interpret gene expression data.
    • Use an appropriate statistical method for hypotheses testing.
    • Produce reports that are written in scientific style.
  • Reprinted by permission from Macmillan Publishers Ltd.

    A Hands-on Introduction to Hidden Markov Models

    Learning Objectives
    • Students will be able to process unannotated genomic data using ab initio gene finders as well as other inputs.
    • Students will be able to defend the proposed gene annotation.
    • Students will reflect on the other uses for HMMs.
  • Adult female Daphnia dentifera. Daphnia spp. make a great study system due to their transparent body and their ease of upkeep in a lab.

    Dynamic Daphnia: An inquiry-based research experience in ecology that teaches the scientific process to first-year...

    Learning Objectives
    Students will be able to:
    • Construct written predictions about 1 factor experiments.
    • Interpret simple (2 variables) figures.
    • Construct simple (2 variables) figures from data.
    • Design simple 1 factor experiments with appropriate controls.
    • Demonstrate proper use of standard laboratory items, including a two-stop pipette, stereomicroscope, and laboratory notebook.
    • Calculate means and standard deviations.
    • Given some scaffolding (instructions), select the correct statistical test for a data set, be able to run a t-test, ANOVA, chi-squared test, and linear regression in Microsoft Excel, and be able to correctly interpret their results.
    • Construct and present a scientific poster.
  • Normal Arabidopsis plants (A) have flat, spatula shaped leaves. asymmetric leaves2 (as2) mutant plants (B) have leaves that are curled under and slightly twisted. asymmetric leaves1(as1) mutant plants (C) have leaves that are curled under and twisted but also have reduced petioles.  In the laboratory activities I present, students analyze the sequence of the as1 and as2 alleles and computationally model the wild-type and mutant proteins. Visualizing the 3-D structure of the proteins helps students understan

    Using computational molecular modeling software to demonstrate how DNA mutations cause phenotypes

    Learning Objectives
    Students successfully completing this lesson will:
    1. Practice basic molecular biology laboratory skills such as DNA isolation, PCR, and gel electrophoresis.
    2. Gather and analyze quantitative and qualitative scientific data and present it in figures.
    3. Use bioinformatics to analyze DNA sequences and obtain protein sequences for molecular modeling.
    4. Make and analyze three-dimensional (3-D) protein models using molecular modeling software.
    5. Write a laboratory report using the collected data to explain how mutations in the DNA cause changes in protein structure/function which lead to mutant phenotypes.
  • pClone Red Makes Research Look Easy

    Using Synthetic Biology and pClone Red for Authentic Research on Promoter Function: Genetics (analyzing mutant...

    Learning Objectives
    • Describe how cells can produce proteins at the right time and correct amount. 
    • Diagram a bacterial promoter with −35 and −10 elements and the transcription start site.
    • Describe how mutational analysis can be used to study promoter sequence requirements.
    • Develop a promoter mutation hypothesis and design an experiment to test it.
    • Successfully and safely manipulate DNA and Escherichia coli for ligation and transformation experiments. 
    • Design an experiment to verify a mutated promoter has been cloned into a destination vector. 
    • Design an experiment to measure the strength of a promoter. 
    • Analyze data showing reporter protein produced and use the data to assess promoter strength. 
    • Define type IIs restriction enzymes.
    • Distinguish between type II and type IIs restriction enzymes.
    • Explain how Golden Gate Assembly (GGA) works.
    • Measure the relative strength of a promoter compared to a standard promoter.  
  • This collage contains original images taken by the course instructor. The images show a microscopic view of stomata on the underside of a Brassica rapa leaf (A), B. rapa plants in their growth trays (B), a flowering B. rapa plant (C), and different concentrations of foliar protein (D). Photos edited via Microsoft Windows Photo Editor and Phototastic Collage Maker.

    A flexible, multi-week approach to plant biology - How will plants respond to higher levels of CO2?

    Learning Objectives
    Students 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).
    Note: Additional, more specific objectives are included with each of the four lessons (Supporting Files S1-S4)
  • Plant ecology students surveying vegetation at Red Hills, CA, spring 2012.  From left to right are G.L, F.D, A.M., and R.P.  Photo used with permission from all students.

    Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced students

    Learning Objectives
    Students 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)
  • 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.
  • Peterson MP, Rosvall KA, Choi J-H, Ziegenfus C, Tang H, Colbourne JK, et al. (2013) Testosterone Affects Neural Gene Expression Differently in Male and Female Juncos: A Role for Hormones in Mediating Sexual Dimorphism and Conflict. PLoS ONE 8(4): e61784. doi:10.1371/journal.pone.0061784

    Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching

    Learning 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.”)
  • Modeling the Research Process: Authentic human physiology research in a large non-majors course

    Learning Objectives
    Students will be able to:
    • Read current scientific literature
    • Formulate testable hypotheses
    • Design an experimental procedure to test their hypothesis
    • Make scientific observations
    • Analyze and interpret data
    • Communicate results visually and orally
  • pClone Red Makes Research Look Easy

    Using Synthetic Biology and pClone Red for Authentic Research on Promoter Function: Introductory Biology (identifying...

    Learning Objectives
    • Describe how cells can produce proteins at the right time and correct amount.
    • Diagram how a repressor works to reduce transcription.
    • Diagram how an activator works to increase transcription.
    • Identify a new promoter from literature and design a method to clone it and test its function.
    • Successfully and safely manipulate DNA and Escherichia coli for ligation and transformation experiments.
    • Design an experiment to verify a new promoter has been cloned into a destination vector.
    • Design an experiment to measure the strength of a promoter.
    • Analyze data showing reporter protein produced and use the data to assess promoter strength.
    • Define type IIs restriction enzymes.
    • Distinguish between type II and type IIs restriction enzymes.
    • Explain how Golden Gate Assembly (GGA) works.
    • Measure the relative strength of a promoter compared to a standard promoter.
  • Students preforming the leaky neuron activity.

    The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cups

    Learning Objectives
    Students 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
  • Model skeleton

    Plotting Cranial and Spinal Nerve Pathways in a Human Anatomy Lab

    Learning Objectives
    • Identify and describe the functions of cranial and spinal nerves
    • Identify cranial and spinal nerve origination points and what structures they innervate
    • Trace the routes that cranial and spinal nerves take throughout the body
  • MA plot of RNA-seq data. An MA plot is a visual summary of gene expression data which identifies genes showing differential expression between two treatments.

    Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using Galaxy

    Learning 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.
  • A A student assists Colorado Parks & Wildlife employees spawning greenback cutthroat trout at the Leadville National Fish Hatchery; B greenback cutthroat trout adults in a hatchery raceway; C tissue samples collected by students to be used for genetic analysis (images taken by S. Love Stowell)

    Cutthroat trout in Colorado: A case study connecting evolution and conservation

    Learning Objectives
    Students will be able to:
    • interpret figures such as maps, phylogenies, STRUCTURE plots, and networks for species delimitation
    • identify sources of uncertainty and disagreement in real data sets
    • propose research to address or remedy uncertainty
    • construct an evidence-based argument for the management of a rare taxon
  • Grow the Gradient game board. A student moves game pieces on the game board as they learn how the loop of Henle creates a salt concentration gradient in the medulla.

    Grow the Gradient: An interactive countercurrent multiplier game

    Learning Objectives
    • Students will be able to simulate the movement of water and sodium at each region of the loop of Henle.
    • Students will be able to associate osmosis and active transport with movement of water/solutes at each region of the loop of Henle.
    • Students will be able to model how the descending and ascending limbs of the loop of Henle maintain a concentration gradient within the medulla.
    • Students will be able to predict the effects of altering normal water and salt movement out of the loop of Henle on the salt concentration of the medulla, urine concentration, and urine volume.
    Advanced Learning Objectives for Extensions
    • Students will be able to predict the impact of the length of the loop of Henle on the magnitude of the concentration gradient within the medulla.
    • Students will be able to predict the length of the loop of Henle in organisms from different habitats.
  • Human karyotype

    Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...

    Learning Objectives
    Students 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
  • Image of a writing center

    Visits to the writing center and office hours provide students structured reflection and low-stakes feedback on...

    Learning Objectives
    • Students will be able to write a lab report that contains a descriptive title, complete and concise abstract, substantive and relevant introduction that includes a testable hypothesis, descriptive methods, description and comparison of results of various testable groups, biological explanation of the results that reflect the testable hypothesis, a conclusion that contains societal implications or scientific impact, and references cited in the document.
    • Students will be able to self-identify weaknesses and strengths of their writing.
    • Students will understand how to utilize office hours and the writing center to receive feedback on their lab reports.
  • 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
  • Fully annotated mitochondrial genome of a lichenized fungal species (Cladonia subtenuis).  This represents a visual representation of the final project result of the lesson plan. Students will submit their annotation to NCBI (GenBank) and upon acceptance of their annotation, they typically add this publicly available resource into their resume.

    A CURE-based approach to teaching genomics using mitochondrial genomes

    Learning Objectives
    • Install the appropriate programs such as Putty and WinSCP.
    • Navigate NCBI's website including their different BLAST programs (e.g., blastn, tblastx, blastp and blastx)
    • Use command-line BLAST to identify mitochondrial contigs within a whole genome assembly
    • Filter the desired sequence (using grep) and move the assembled mitochondrial genome onto your own computer (using FTP or SCP)
    • Error-correct contigs (bwa mem, samtools tview), connect and circularize organellar contigs (extending from filtered reads)
    • Transform assembled sequences into annotated genomes
    • Orient to canonical start locations in the mitochondrial genome (cox1)
    • Identify the boundaries of all coding components of the mitochondrial genome using BLAST, including: Protein coding genes (BLASTx and tBLASTX), tRNAs (proprietary programs such as tRNAscan), rRNAs (BLASTn, Chlorobox), ORFs (NCBI's ORFFinder)
    • Deposit annotation onto genome repository (NCBI)
    • Update CV/resume to reflect bioinformatics skills learned in this lesson
  • Structure of protein ADA2

    Understanding Protein Domains: A Modular Approach

    Learning Objectives
    • Students will be able to compare protein sequences and identify conserved regions and putative domains.
    • Students will be able to obtain, examine, and compare structural models of protein domains.
    • Students will be able to interpret data on protein interactions (in vitro pull-down and in vitro and in vivo functional assays)
    • Students will be able to propose experiments to test protein interactions.
  • DNA

    Using CRISPR-Cas9 to teach the fundamentals of molecular biology and experimental design

    Learning Objectives
    Module 1
    • Generate a testable hypothesis that requires a creative design of reagents based on critical reading of and review of prior research.
    • Demonstrate proficiency in using molecular cloning software to analyze, manipulate and verify DNA sequences.
    • Predict the downstream effect on the mRNA and protein after successfully inserting a DNA repair template into the genome of a cell/organism.
    • Compare and contrast the processes of DNA duplication and PCR.
    • Demonstrate the ability to design primers to amplify a nucleotide sequence.
    • Analyze and evaluate the results of DNA agarose gel electrophoresis.
    Module 2
    • Identify the key features in genomic DNA, specifically those required for CRISPR-Cas9 mediated gene edits.
    • Explain how compatible ends of DNA are used to produce recombinant DNA in a ligation reaction.
    • Explain the chemical principles behind plasmid DNA purification from bacterial cultures.
    • Devise a strategy to screen clones based on antibiotic selection and the mechanism of digestion by DNA endonucleases.
    • Predict and evaluate the results of a diagnostic digest.
    Module 3
    • Explain the chemical principles behind DNA purification using phenol-chloroform extraction and ethanol precipitation.
    • Explain the key differences between DNA duplication and transcription.
    • Demonstrate the ability to perform lab work with sterile technique.
    • Compare and contrast the results of a non-denaturing vs. denaturing agarose gel.
    • Evaluate the results of a denaturing agarose gel.
    Module 4
    • Design and implement an experiment that tests the CRISPR-Cas9 principle.
    • Predict the outcome of a successful in vitro Cas9 digest.
    Presentation of Data Post Lesson
    • Summarize important background information on gene of interest from analysis of primary literature.
    • Produce figures and figure legends that clearly indicate results.
    • Organize and construct a poster that clearly and professionally displays the important aspects of the lesson.
    • Demonstrate understanding of the lesson by presenting a poster to an audience in lay terms, mid-level terms, or at an expert level.
    • Demonstrate understanding of procedures by writing a formal materials and methods paper.
  • Students using the Understanding Eukaryotic Genes curriculum to construct a gene model. Students are working as a pair to complete each Module using classroom computers.

    An undergraduate bioinformatics curriculum that teaches eukaryotic gene structure

    Learning Objectives
    Module 1
    • Demonstrate basic skills in using the UCSC Genome Browser to navigate to a genomic region and to control the display settings for different evidence tracks.
    • Explain the relationships among DNA, pre-mRNA, mRNA, and protein.
    Module 2
    • Describe how a primary transcript (pre-mRNA) can be synthesized using a DNA molecule as the template.
    • Explain the importance of the 5' and 3' regions of the gene for initiation and termination of transcription by RNA polymerase II.
    • Identify the beginning and the end of a transcript using the capabilities of the genome browser.
    Module 3
    • Explain how the primary transcript generated by RNA polymerase II is processed to become a mature mRNA, using the sequence signals identified in Module 2.
    • Use the genome browser to analyze the relationships among:
    • pre-mRNA
    • 5' capping
    • 3' polyadenylation
    • splicing
    • mRNA
    Module 4
    • Identify splice donor and acceptor sites that are best supported by RNA-Seq data and TopHat splice junction predictions.
    • Utilize the canonical splice donor and splice acceptor sequences to identify intron-exon boundaries.
    Module 5
    • Determine the codons for specific amino acids and identify reading frames by examining the Base Position track in the genome browser.
    • Assemble exons to maintain the open reading frame (ORF) for a given gene.
    • Define the phases of the splice donor and acceptor sites and describe how they impact the maintenance of the ORF.
    • Identify the start and stop codons of an assembled ORF.
    Module 6
    • Demonstrate how alternative splicing of a gene can lead to different mRNAs.
    • Show how alternative splicing can lead to the production of different polypeptides and result in drastic changes in phenotype.
  • Using the Cell Engineer/Detective Approach to Explore Cell Structure and Function

    Learning Objectives
    Students will be able to:
    • Identify the major cell organelles
    • List the major functions of the organelles
    • Predict how changes in organelle/cell structure could alter cellular function
    • Explain how overall cellular function is dependent upon organelles/cell structure
    • Relate cell structure to everyday contexts
  • Using QIIME to Interpret Environmental Microbial Communities in an Upper Level Metagenomics Course

    Learning Objectives
    Students 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.