SWE4016/DHC3003, Bio-Computing (Introduction to Computational Biology)
2026, 1st Term
Class Hours: Tue/Thu 9:00am - 10:50am
Classroom: Convergence Hall 319
Professor: Young-Rae Cho (email: youngcho@yonsei.ac.kr)
Office: Chang-328
TA: Gwang-Hyeon Yun (email: ghyun0130@yonsei.ac.kr)
Office: Chang-327
Course Web Page: https://ads.yonsei.ac.kr/faculty/biocomputing/
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Description
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Introduction to computational issues on analyzing biological data. The focus of this course is on design and evaluation of algorithms with applications to bioinformatics, and programming to manipulate biological data using Python. Topics include (1) sequence alignment, (2) pattern matching and finding, (3) phylogenetic algorithms, and (4) gene clustering and classification.
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Objectives
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- To understand the basic concepts and techniques on Computational Biology and Bioinformatics.
- To develop computational skills of designing algorithms to analyze biological data.
- To gain experience of programming to manipulate biological data using Python.
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Prerequisites
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- CSE2003/SWE2001, Data Structures
- Python programming skills
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References
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- Course material (written in English)
- An Introduction to Bioinformatics Algorithms, by Neil C. Jones and Pavel A. Pevzner, The MIT Press
- Algorithms in Bioinformatics: A Practical Introduction, by W.-K. Sung, CRC Press
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Assignments
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- 8 programming assignments using Python
- Submission: source codes via LearnUs during practical sessions
- Late-submission is NOT accepted
- In cases of excused absences from practical sessions, grades will be assigned as follows: 70% of the average assignment score for the first excused absence, 30% for the second excused absence, and 0% for the third and any subsequent excused absences.
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Exam
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- Midterm Exam (April 23, 9:00am - 10:40am): offline, closed-book
- Final Exam (June 11, 9:00am - 10:40am): offline, closed-book
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Grading
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- Programming Assignments: 40%
- Midterm Exam: 25%
- Final Exam: 25%
- Attendance & Participation: 10%
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Policies
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- According to the university policy, absences more than 30% will cause getting an F as the final grade of the course no matter what scores are obtained in exames and assignments. An official excuse letter will be accepted.
- All programming assignments must be independent work. Any form of academic misconduct, including the unauthorized use of AI tools, in programming assignments or exams will result in a failing grade (F) for this course, in accordance with university regulations.
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Topics & Tentative Schedule