Same school, new name. The School of Informatics and Computing is changing its name effective January 11, 2023. Learn more about the name change

INFO-B 436 Computational Methods for Biomedical Informatics

3 credits

  • Prerequisites: PBHL-B 302 Biostatistics of Informatics and INFO-I 223 Data Fluency
  • 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 pros and cons 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.

    Syllabi