You are here
Search found 3 items
- (-) Remove Bioinformatics filter Bioinformatics
- (-) Remove Lab filter Lab
- (-) Remove Upper Level filter Upper Level
- (-) Remove Develops supportive community of learners filter Develops supportive community of learners
- (-) Remove Information flow, exchange and storage filter Information flow, exchange and storage
A CURE-based approach to teaching genomics using mitochondrial genomesLearning 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
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
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.