CBMF W 4761

Computational Genomics

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.

When : Mon, Wed, 2:40pm to 3:55pm ;
Where : Eng Terrace 253
By who : Itsik Pe'er, office hours: 9-10
Teaching assistant : Sasha Gusev