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Introduction to Computational Biology.
Course info
- Code: Bioe131/231
- Title: Introduction to computational biology
- Instructor: Ian Holmes (office hours: 11am-noon Wednesdays, 374C Stanley Hall; or by appointment)
- GSI: Josh Kittleson, 1171 Etcheverry Hall (office hours: 5:30-6:00pm Mon & Wed and by appointment)
- When:
- Instructor blog -- please do leave comments/questions
- Final grading scheme
- 75% homework assignments
- Lowest homework grade will be discarded
- 25% final project presentation
- To take place 12/5, 12/7 and 12/10
- You may also, at your option, submit a take-home exam. If the grade for this exam is higher than for your final presentation, it will be used instead. The exam questions will be posted no later than 12/1. Due to the timing it will not be possible to provide exam grades prior to the final presentation.
- Extensions/Alternate Exam Dates:
- Requests for extensions on homework due dates must be submitted to Ian Holmes 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 Ian Holmes 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.
Student wiki
Announcements
- Final grades are now posted on bearfacts. Happy holidays -- IanHolmes - 13 Dec 2007
- Here are the model solutions to the final exam, including the grading scheme -- IanHolmes - 11 Dec 2007
- The take-home final paper can be downloaded here if you did not pick one up in class -- IanHolmes - 01 Dec 2007
- Please sign up on the FinalPresentationSchedule page if you want to reserve a timeslot -- IanHolmes - 28 Nov 2007
- FinalExam review on Wednesday 11/28 -- IanHolmes - 21 Nov 2007
- Take-home FinalExam will be given out on Friday 11/30 (at end of class) and must be returned by Monday 12/3 (also at end of class) -- IanHolmes - 21 Nov 2007
- FinalProject now posted! -- IanHolmes - 06 Nov 2007
- Please sign up for the Jgi Tour if you can go -- IanHolmes - 03 Nov 2007
- There is now a class blog summarizing the content of each lecture. Please do leave comments/questions if you have them. -- IanHolmes - 07 Sep 2007
- Please register to get yourself a page on the Fall07 student wiki before the second lab. -- IanHolmes - 29 Aug 2007
Syllabus
Approximate sequence of lectures:
- Introductory case study
- Overview of syllabus; available means of assessment..
- group & individual presentations; literature reviews; class participation; homework; exam(s); project
- Review of fundamental molecular biology
- Biophysical principles of RNA and protein folding
- Overview of biological databases
- Introduction to Unix
- Introduction to Perl programming: loops, variables, subroutines; file manipulation; data structures
- Assemblers, compilers, interpreters & virtual machines: machine code, C, Perl and Java
- Sequence alignment algorithms: Needleman-Wunsch, Smith-Waterman, Gotoh, BLAST
- Probabilistic inference; Bayes' theorem; experimental error; expectation and variance
- Quick refresher in basic distributional analysis...
- Basic combinatorics; binomials and multinomials
- Geometric, exponential, Poisson distributions
- Gaussian distribution; mixture distributions
- Quantitative measures of information; illustration via data compression
- Log-likelihood ratios and substitution matrices; coding & cryptography
- Probabilistic models for sequence motifs; "sequence logos"
- Algorithmic complexity & "big-O" notation: examples from compbio
- Finite state machines; multiple alignment; phylogenetic reconstruction
- Rate variation, evolutionary trace and phylogenetic profiling; applications to design
- Structural biology, protein structure prediction, protein design
- Clustering algorithms: K-means, K-medians; application to microarray data analysis
- Sequence assembly & metagenomics; examples (human microbiome; bioenergy)
- Genome annotation; biological ontologies, pathway databases
- Biophysics of synthetic biology: RNA folding kinetics & viral genome design
- Guest lectures: computational biology at Berkeley
Notes and handouts
The following handouts should be regarded as an incomplete summary of the lecture content.
Due to the breadth of this class, the fast-changing nature of computational biology and the inclusion of several guest lectures,
the content (and sequence) of lectures changes subtly each year.
It is near-impossible to provide a single handout, ahead of time, that exactly matches the lectures and practicals taught in class.
The following represents our best effort to predict the content this year, based on previous years.
Again, please note that there will be some additional examinable content in the lectures that is not included in the handouts.
Slides
Accompanying notes
The following contain condensed versions of some of the info on the slides:
The following may be regarded as additional review/summary material:
- Sample Midterm questions (note: in 2007 we dropped the midterm in favor of programming exercises, but these may still be useful)
- Some illustrations of Relative Entropy
Lab practicals
Homework exercises
Homework exercises will be assigned in labs and posted on the individual lab pages.
Programming assignments will be graded both for form (style) and function (correctness). Stylistic expectations will be outlined on the style guidelines page by the time the first assignment is given.
Textbooks
No textbook purchase is required to take the class.
References to the following textbook (which can be freely downloaded) appear occasionally as recommended reading:
- The MacKay Book: MacKay, DJC. Information Theory, Inference and Learning Algorithms. ISBN:0521642981
- Can be downloaded from here (copyright grants permission to view but not print)
The following Perl books from O'Reilly may be a useful supplement to what's taught in class:
- The following are the two "classic" Perl tutorial and reference books:
- The "Perl for Bioinformatics" series have more bioinformatics-oriented examples:
Other resources
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