Term Taken: 2019 Fall
Instructor: Prof. Kevin Yip Yuk Lap
Grading Scheme
Original Scheme:
- Assignments (45%)
- Ureply Quiz (5%)
- Midterm Exam (20%)
- Final Exam (30%)
Scheme for 2019 Course Cancellation:
- Assignments (54%)
- Ureply Quiz (6%)
- Midterm Exam (40%)
Topics Covered
- Optimal sequence alignment.
- Heuristic sequence alignment (BLAST/FASTA).
- Short read alignment (Suffix Trie, BWT).
- Sequence assembly (de Bruijn graph).
- Sequence motif models, k-mer counting.
- Hidden Markov models.
- Phylogenetic tree reconstruction.
- Genetic data inference.
- Clustering algorithms.
- RNA secondary structure prediction.
Review
This course is a combination of biology and computer science, but the focus is on the algorithms rather than the biology knowledge.
Various algorithms for solving bioinformatics problems were introduced, compared, and analyzed in the class. And most interestingly, almost all of the algorithms introduced were also useful outside the fields of bioinformatics. For example, we were taught the dynamic programming approach to solve the global and local alignment problem of gene sequences and it is also an indispensible algorithm in the fields of natural language processing. Also, towards the end of the semester, some machine learning algorithms were also taught. Thus, if you are interested in designing and analyzing algorithms, or learning some machine learning basics, this course is for you.
As for the homework, we had to implement selected algorithms using either Java, Python, C++ or C and submit it through an online judge system. It was challenging but extremely rewarding, since you would get a much deeper understanding on the algorithms once you implement them.
Prof. Yip is a great instructor, he explains everything clearly and makes sure all prerequisite knowledge is covered before moving on to the algorithm itself. The lectures are extremely enjoyable and I highly recommend this course for all computer science students even if you are not into biology.