BIOE 131/231 - Introduction to Computational Biology
Note: this is the page for the Fall 2005 class. For Fall 2006, please go to the new BioE131 page.
- (11/30/05 AngiChau): This week's lab (ImmuneSystemDynamics) is the last homework assignment. We will be dropping your lowest homework score, so whether you complete this week's assignment is your decision. Remember that you can check all your scores on Blackboard. Due to Thanksgiving craziness, I have not graded the last assignment yet (sorry!) but I will try to do so before the end of this week. If you're waiting for your score on the last assignment to decide whether you should complete this week's assignment or not, you should have your answer by Friday.
Remember that your mid-project progress report for the project is due THIS Friday. Please email your report (one per team) to both myself and Prof Holmes.
Project presentations will begin next Monday and continue on Wednesday, as needed. ALL teams must be ready to present on Monday because we will be randomly choosing teams to present. You should aim for a presentation that is 10 minutes long.
- (11/23/05 IanHolmes): In the next week or two, you will be asked to fill out a student course evaluation form. This is your chance to offer constructive (or vituperative) feedback on the design and conduct of this course, in private. In the meantime, if you want to offer similar feedback in public (but still anonymously), please go ahead and edit the UndergraduateClassFeedback wiki page. Think there should be much less Perl? More time for projects? Liked the practicals? Hated the midterm? Go ahead and comment on the UndergraduateClassFeedback page.
- Code: Bioe131/231
- Title: Introduction to computational biology
- Instructor: IanHolmes (Office Hours: Wed 11-noon, 465 Evans Hall, or by appointment)
- GSI: AngiChau (Office Hours: Mon 4-5pm, 1111 Etcheverry Hall)
- When: Fall 2005
- Lectures: MWF, 3-4pm, 310 Hearst Mining Memorial Building
- Lab: Wed 4-5:30pm, 1171 Etcheverry Hall
- Grading Policy:
- 40% Homework
- 20% Mid-term
- 40% Final Project
- Important dates:
- 10/19: In-class midterm exam
- 11/9: Final project assignments
- 12/5, 12/7: Final project presentations
- 12/9: Final project write-up due
- Extensions/Alternate Exam Dates:
- Requests for extensions on homework due dates must be submitted to IanHolmes via email at least 2 days before homework due date, clearly stating reason(s) for request.
- Requests for alternate exam dates must be submitted to IanHolmes via email as soon as possible, clearly stating reason(s) for request. An alternate date should only be requested under extreme circumstances, such as family emergencies, major illness, etc. Otherwise, please plan on attending the scheduled exam times.
This course is a tutorial introduction to bioinformatics, computational biology, systems biology,
practical computation, information theory and probabilistic models.
While it is primarily aimed at undergraduates, graduate students can attend for credit
if they demonstrate substantial advances in fulfilling the programming or other exercises.
(A substantial advance is defined as "software that enhances the value of the course for future years"
- Teach basic probability and Markov chains for computational biology
- Illustrate the broad range of compbio via structured exercises
- Introduce practical Unix skills
The course will cover/review basic probability/stats material including
- Basic probability
- Bayes' theorem, conditional and joint probability
- discrete and continuous distributions
- expectation, variance and covariance; combining experimental errors
- Basic information theory
- Simple combinatorics
- permutations, factorials
- combinations, the combinatorial coefficient
- Simple distributions
- Review of linear algebra: eigenvalues and eigenvectors
- Solution of a diagonalizable system of linear ordinary differential equations
- The k-means clustering algorithm
- Mixture of Gaussians interpretation
- Brief introduction to Markov chains
- Brief introduction to graphical models
A working knowledge of basic molecular biology (e.g. the central dogma)
More advanced concepts (e.g. RNA structure, gene regulation)
will be introduced throughout the course, to motivate the
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