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- (-) Remove Introductory Biology filter Introductory Biology
- (-) Remove Assessment of individual student performance filter Assessment of individual student performance
- (-) Remove Analyzing data filter Analyzing data
- (-) Remove Information flow, exchange and storage filter Information flow, exchange and storage
Follow the Sulfur: Using Yeast Mutants to Study a Metabolic PathwayLearning ObjectivesAt the end of this lesson, students will be able to:
- use spot plating techniques to compare the growth of yeast strains on solid culture media.
- predict the ability of specific met deletion strains to grow on media containing various sulfur sources.
- predict how mutations in specific genes will affect the concentrations of metabolites in the pathways involved in methionine biosynthesis.
Antibiotic Resistance Genes Detection in Environmental SamplesLearning ObjectivesAfter completing this laboratory series, students will be able to:
- apply the scientific method in formulating a hypothesis, designing a controlled experiment using appropriate molecular biology techniques, and analyzing experimental results;
- conduct a molecular biology experiment and explain the principles behind methodologies, such as accurate use of micropipettes, PCR (polymerase chain reaction), and gel electrophoresis;
- determine the presence of antibiotic-resistance genes in environmental samples by analyzing PCR products using gel electrophoresis;
- explain mechanisms of microbial antibiotic resistance;
- contribute data to the Antibiotic Resistance Genes Network;
- define and apply key concepts of antibiotic resistance and gene identification via PCR fragment size.
Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issuesLearning ObjectivesStudents will be able to:
- Describe various parameters of air quality that can negatively impact human health, list priority air pollutants, and interpret the EPA Air Quality Index as it relates to human health.
- Identify an air quality problem that varies on spatial and/or temporal scales that can be addressed using publicly available U.S. EPA air data.
- Collect appropriate U.S. EPA Airdata information needed to answer that/those questions, using the U.S. EPA Airdata website data mining tools.
- Analyze the data as needed to address or answer their question(s).
- Interpret data and draw conclusions regarding air quality levels and/or impacts on human and public health.
- Communicate results in the form of a scientific paper.
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.
A clicker-based case study that untangles student thinking about the processes in the central dogmaLearning ObjectivesStudents will be able to:
- explain the differences between silent (no change in the resulting amino acid sequence), missense (a change in the amino acid sequence), and nonsense (a change resulting in a premature stop codon) mutations.
- differentiate between how information is encoded during DNA replication, transcription, and translation.
- evaluate how different types of mutations (silent, missense, and nonsense) and the location of those mutations (intron, exon, and promoter) differentially affect the processes in the central dogma.
- predict the molecular (DNA size, mRNA length, mRNA abundance, and protein length) and/or phenotypic consequences of mutations.