Nov 26, 2022  
2019-2020 Graduate Catalog 
2019-2020 Graduate Catalog [ARCHIVED CATALOG]

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CS 540 - Algorithms for Biological Data Analysis (Put on reserve 9/16/19)

The course introduces the algorithms used in bioinformatics. (Put on reserve 9/16/19, will go inactive 8/24/22)

Prerequisite: CS 529.


Learner Outcomes:
Upon successful completion of this course, the student will be able to:

  • Categorize biological pattern analysis through pattern matching.
  • Evaluate genomic problems and choose and employ an appropriate solution technique (e.g., patterns alignment, gradient descent, or expectation maximization).
  • Design and implement probabilistic graphical models using Bayesian inference and Bayesian analysis.
  • Implement and evaluate Markov Chain solutions using a Hidden Markov Model.
  • Evaluate Markov Chain Monte- Carlo methods as a means of applying stochastic simulation in bioinformatics.

Learner Outcomes Approval Date:

Anticipated Course Offering Terms and Locations:

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