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INFO-B 536 Computational Methods for Biomedical Informatics

3 credits

  • Prerequisites: None
  • Delivery: On-Campus
  • This course covers algorithm design, algorithm analysis, and complexity analysis and their applications in biomedical informatics.

    Learning Outcomes

    1. Evaluate common problems in biomedical informatics, such as sequence alignment, genome arrangement, and peptide identification.
    2. Analyze time and space complexity and other theoretical concepts used in algorithm analysis and complexity analysis.
    3. Apply abstract data structures to solve problems in biomedical informatics.
    4. Compare the advantages and disadvantages of computational methods for a biomedical problem and choose appropriate methods.
    5. Evaluate the similarity between new problems and existing problems and adapt computational methods designed for existing problems to new problems.
    6. Design computational methods using a greedy, brute-force, divide-and-conquer, or dynamic programming approach.
    7. Evaluate biomedical problems using example-based problem-solving skills and iterative refinement skills.
    8. Design and perform experiments for evaluating computational methods and publicly present experimental results.