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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.
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.
Linking Genotype to Phenotype: The Effect of a Mutation in Gibberellic Acid Production on Plant GerminationLearning ObjectivesStudents will be able to:
- identify when germination occurs.
- score germination in the presence and absence of GA to construct graphs of collated class data of wild-type and mutant specimens.
- identify the genotype of an unknown sample based on the analysis of their graphical data.
- organize data and perform quantitative data analysis.
- explain the importance of GA for plant germination.
- connect the inheritance of a mutation with the observed phenotype.