Administration
When: Tue, Thu, 10:35am to 11:50am ; Spring 2012
Where: Mudd 1127
By who: Itsik Pe'er, office hours: Thu 12:00-13:00
Teaching assistant: Arthi Ramachandran
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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