Mar 20, 2023  
2022-2023 Academic Catalog 
    
2022-2023 Academic Catalog
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BIOT 620/6206 - Computational Genomics and Transcriptomics (3 cr.)



Prerequisites
  

Description
The course is designed to provide graduate students with the essential concepts and skills for processing, analyzing, and visualizing biologcial data generated by modern high-throughput transcriptomic and genomic technologies such as microarray and next-generation sequencing. The open-source statistical platform R and the BioConductor package will be used throughout the course for the practical sessions. The course will focus on how to extract meaningful information from microarray and RNA-Seq data (e.g., differentially expressed genes, alternative splice forms, and polymorphism). Different data visualization methods will be covered from simple summarizing graphs to interaction networks of cellular elements. Practical exercises will use publically published data and simulated data with applications crossing from cancer genomics to environmental genomics. Target audience is biomedical and computational sciences graduate students and postdoctoral researchers.

When Offered
Offered in fall.



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