CPSC 445: Algorithms for Bioinformatics, 2016 Winter 2
[Connect: Lecture notes, Assignments, Project,
Grades]
Announcements
- The second round of presentations will take place on April 6.
- The final exam is on April 12, 12p-2.30p in DMP110.
- You can submit the bonus question of Assignment 5 until 10PM on April
14. It's worth 15 points.
Lectures: |
Tuesday, Thursday 9:30-11:00a, DMP 301 |
Instructor: |
Jan Manuch
jmanuch AT cs dot ubc DOT ca
Office: ICCS 247
Office Hours: Tuesday 2:30p-3.30p and Thursday 11:00a-12:00p
|
TAs: |
Eugene Xie
eugene DOT t DOT xie AT alumni DOT ubc DOT ca
Office Hours: Thursday 1:00p-2:00p in ICCS X153
|
Massih Khorvash
massih DOT khorvash AT ubc DOT ca
Office Hours: Thursday 4:00p-5:00p in ICCS X151
|
If you cannot make any of the office hours, please send one of us a message to arrange another time to meet.
About this course:
Bioinformatics involves the application of computational methods to answer or provide insight on questions in molecular biology. This course provides an introduction to the design and analysis of algorithms for bioinformatics applications. Topics covered will include sequence alignment (including multiple sequence alignment), phylogenetic tree reconstruction (parsimony and distance-based methods), and basic folding algorithms for RNA sequences. Algorithmic techniques that will be discussed include dynamic programming and heuristic search methods, as well as combinatorial algorithms for exploration of graphs and trees. Statistical models of molecular sequence and structure, such as hidden Markov models, and associated algorithms, will also be covered.
Prerequisites:
CPSC 320 and six credits of BIOL beyond BIOL 111, or equivalent. Experience with design and analysis of algorithms is essential for this course. Related texts listed below, such as
Molecular Biology of the Cell, will be useful for those who need to catch up on biological background. The algorithms texts by
Cormen et al. and by
Kleinberg and Tardos provide useful background on combinatorial algorithms, including graph algorithms and dynamic programming algorithms.
Strongly Recommended Textbook:
Durbin, Eddy, Krogh, Mitchison, Biological Sequence Analysis. Cambridge University Press, 1998.
Alternative Textbooks:
Cormen, Thomas H.; Leiserson, Charles E., Rivest, Ronald L., Stein, Clifford (2009) [1990]. Introduction to Algorithms (3rd ed.). MIT Press and McGraw-Hill. ISBN 0-262-03384-4.
Jon Kleinberg and Eva Tardos. 2005. Algorithm Design. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.
Bruce Alberts, Alexander Johnson, Julian Lewis, Martin Raff, Keith Roberts, and Peter Walter. 2010. Molecular Biology of the Cell (6th Ed) New York: Garland Science; 2002.
Student Evaluation and Grading
Final grades will be determined as follows:
- homework assignments (approx. five overall)
- ca. 35%
- group project (one project with two milestones: proposal and presentation)
- ca. 30%
- final examination
- ca. 35%
Missed Course Work and Academic Misconduct:
- University
policy and departmental
guidelines on incompletes and academic misconduct will be followed
strictly.
- All work on the exams must be entirely your own, with no discussion or aid from anyone else.
- Homework assignments can be discussed in groups, but you must write up your own solutions in your own words.
- Group project is handed in with one document and/or presentation per group.
- Late hand-ins of assignments will not be accepted.
- Missed course work (assignments, project proposal, etc.) can only be excused
in the case of officially documented medical reasons (doctor's note required).