Administration
When: Tue, Thu, 10:35am to
11:50am ; Spring 2011
Where: Mudd 454
By who: Itsik Pe'er, office hours: Tue
12:30-13:30
Teaching assistant: Sasha
Gusev, Snehit
Prabhu
What for: 3 credit points
For who: Graduate/advanced undergraduate students of relevant fields.
Although the course is listed in Computer Science, cross enrollment by
students with biomedical background is encouraged.
Pre-requisite: Each student is expected
to be an independent programmer
Technology for obtaining DNA sequences have been consistently improving
faster than Moore's law. This has opened a wealth of computational challenges
in weaving the heaps of straw of DNA sequence data into gold of biological insight.
The class serves as an introduction to computational genomics, explaining the
basic challenges and teaching the general computer-science tools to tackle
them. This course is intended to introduce students of both computational and
bio-medical skill sets to current quantitative understanding of genomics and
prepare them to computational research or industrial development in the
field. Questions we'll touch on include :
- How to get the
sequence of your genome?
- How to model different
but similar genes?
- How to model the same
but mutated gene?
- How to infer the tree
of life?
- What do we learn from
comparing genomes?
- How to find genes and
signals in DNA?
- Why is there variation
within a species?
- Do genes determine
traits?
- How does natural selection
work?
The
computational toolbox discussed includes parameter inference, likelihood
analysis, hidden Markov and other graphical models, eigenvalue
decompositions, and classification problems.
- Week 1 Introduction to
genomics, statistics
- Week 2 Alignment of
high-throughput sequence reads with exact string-matching
- Week 3 Homology, repeats and
gene families by similarity searches
- Week 4 Neutral sequence
evolution by Markov models
- Week 5 Phylogenetics and
tree reconstruction
- Week 6 Speed of evolution
(Markov models)
- Week 7 Coalescent models
(MCMC)
- Week 8 Midterm
- Week 9 Projects Outline
- Week 10 Ancestral
recombination graphs
- Week 11 Genetic mapping
(hypothesis testing)
- Week 12 Projects midpoint
- Week 13 Negative, Selection
- Week 14 Projects final
presentation
- Q: I'm a Computer
Science student with no background in biology. Can I take the course?
A: Sure. The necessary biological background will be given in
condensed form at the first meeting, and then supplemented when
necessary. The course is designed for a small, interactive class, with
each student having enough weight to affect the level of background
given.
- Q: I'm a student in
Medical Informatics/Biological Sciences with no background in computing.
Can I take the course?
A: Probably not. You will need to be able to write your
own programs. Some background in probability/statistics/biometry is an
advantage.
- Q: How is the course
graded?
A: A combination of homework assignments, late midterm and a
final project.
- Q: What are the projects
like?
A: An example may be giving you a 5 year-old paper, asking you to
read, understand, implement the computational method so that it can work
on today's data (which is often orders of magnitude larger and more
complex), analyse what you find, and write up what you find. Submission
will include:
- Any code you've
developed
- A detailed written
report
- An executive summary
of 5 slides.
- Q: What are the office
hours?
A: Wed morning. See my contacts.
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