Administration
When: Mon, Wed, 2:40pm to 3:55pm ; Spring 2009
Where: TBD
By who: Itsik Pe'er, office hours: Mon 1:30-2:30, Wed 4-5
Teaching assistant: TBD
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: The students are expected to be an independent programmer
Abstract
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.
Tentative Program - under construction
- Week 1 Intruction to genomics
- 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 Ancestral recombination graphs
- Week 9 Midterm
- Week 9 Projects
- Week 10 Genetic mapping (hypothesis testing)
- Week 11 Negative, Selection
- Week 14 Projects final presentation
FAQ
- 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:
Just before/after the times of class. See my contacts.