CMPUT 606: Optimization in Bioinformatics (Winter 2025)


eClass: https://canvas.ualberta.ca/courses/18442

Overview:
An introduction to the classic and current research in Bioinformatics and Computational Biology allowing you to get some hands-on experience by working on a course project. We will introduce various formulated optimization problems and you will find various computing techniques applicable.

Course Objectives:

  • Learn some classic and currently hot research topics in bioinformatics and computational biology;
  • learn computing techniques for this area of research;
  • be familiar enough to explain these topics to others and understand what contributions you could make.

Student Academic Integrity Policy
Student Conduct Policy
Department Course Policies

Time
Monday
Tuesday
Wednesday
Thursday
Friday
noon
 
1:00pm
 
2:00pm
 
Possible project meetings
(by appt)
 
 
Lecture B1 (GSB 8-11)
3:00pm
Possible project meetings
(by appt)
 
4:00pm
 

Recording of teaching is permitted only with the prior written consent of the instructor or if recording is part of an approved accommodation plan.


Recommended readings (no required textbook):

  • L. Gonick and M. Wheelis (1991). "The Cartoon Guide to Genetics". Harper Perennial.
  • A. M. Lesk (2002). "Introduction to Bioinformatics". Oxford Univ. Press.
  • D. Gusfield (1997). "Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology". Cambridge Univ. Press.
  • P. Baldi and S. Brunak (2001). "Bioinformatics, the Machine Learning Approach". The MIT Press.
  • T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein (2009). "Introduction to Algorithms (Third Edition)". The MIT Press.

Lecture Schedule:

Week Date Lecture Topics
1 Jan 10 Course overview;
discussion on how to run the course (below is one version);
biology background introduction
2 Jan 17 Sequencing
3 Jan 24 Sequence and string comparison
Exercise #1 (10%) on sequencing due 26th
4 Jan 31 Phylogenetic analysis
Exercise #2 (10%) on sequence comparison due 2nd
5 Feb 7 Genotyping and genome-wide association study
Exercise #3 (10%) on phylogenetic analysis due 9th
6 Feb 14 Gene expression and data analysis
Exercise #4 (10%) on genotyping/halpotyping due 16th
7 Feb 21 Family Day, Reading Week
8 Feb 28 Missing data imputation
Exercise #5 (10%) on clustering, classification, regression due 2nd
9 Mar 7 Student project proposal presentations
  1. 2:10pm (see Google Drive)
  2. 2:40pm
  3. 3:10pm
  4. 3:40pm
  5. 4:10pm
10 Mar 14 Student project proposal presentations
  1. 2:10pm (see Google Drive)
  2. 2:40pm
  3. 3:10pm
  4. 3:40pm
  5. 4:10pm
Course project review, proposal due 16th
11 Mar 21 Protein properties
12 Mar 28 Protein structure comparison, determination, and prediction
13 Apr 4 Proteomics and metabolomics
Course project final report due 9th


Grading Scheme:

  1. Check my marks
  2. There is no exam.
  3. Mark distribution:
    • 50%  5 weekly programming exercises and numerical experiments (10% each);
    • 20%  course project proposal + presentation (background, existing work, methods, expected results, rationale);
    • 30%  course project final report (literature review excluded).
  4. Notes:
    • Each student to create a GoogleDrive (w/sub-directories) containing all your work to share with your instructor;
      New: eClass has been created and please try to make submissions there;
    • a `readme` file (or `makefile`) to run your program and replicate your results.
      (Failing to replicate your results is automatically a zero.)
    • A presentation is worth half of the marks;
    • One can choose to present their project during Weeks 11-13, if highly aligning with lecture topics.

 

Disclaimer: Any typographical errors in this Course Outline are subject to change and will be announced in class.

 

  Last modified: January 23 2025 11:30:36  © Guohui Lin