CSCI 6802

Bioinformatics Algorithms

Lec 01 selected

The discipline of bioinformatics applies sophisticated computational and statistical techniques to problems in the biological domain. This course will focus on a few biosequence-related challenges in depth, examining the complexity and efficiency of different approaches, the relationship between statistical optimality and biological reality, and the consistency (or lack thereof) among methods.

Sections

Lecture

From the syllabus

From the Winter 2026 syllabus by Finlay Maguire. Winter 2027 is taught by Beiko R., so details may differ. Open the PDF

Grading

60%Practical assignments (4)15% each
25%Written paper reviewDue April 8
15%Oral presentationDuring final lecture slots

Course rules

Late work
Assignments lose 20% per day; work over five days late receives zero, though feedback may be requested.
Collaboration
Collaboration is not permitted on assignments or the final project report.
Submission
Submit assignments to Brightspace as PDFs; incorrect formats receive zero after the first assignment.
Generative AI
AI may be used to explore concepts, but submitted work must be written by the student and not generated by AI.
Absences
Student declarations of absence are not accepted.

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