Guidelines for Programming, Data Analysis or Experimental Algorithmics Projects

[Problem area] [Proposal] [Presentation and final paper]

Problem area: Analysis of a biomolecular problem or data set. This can include designing and implement your own code or applying an existing program to a new biological dataset.

The goal of the project is to expose you to emerging problems in computational genomics - computational problems that are not covered in the lectures and have not yet made their way into text books. For computational projects, a second goal is to give you hands on experience in planning a research project and working with real data. You should consider this an opportunity to do exploratory research.

In evaluating your project, I will consider both what you accomplished and what you learned from the project. This can include learning about a new problem or area in genomics, learning how to work with a particular type of data, gaining familiarity with new algorithms or methods, designing new algorithms or methods. A project that does not succeed in accomplishing what was originally proposed can still get a high grade, if the approach was innovative and the participants are able to explain what went wrong and suggest how the problems could be corrected.


Proposal:

If I am concerned that your proposed approach contains a major stumbling block, I will ask you to revise it.


The paper and presentation:

A final presentation and a 2-3 page summary of work performed and results obtained.



Last modified: September 21, 2004.
Maintained by Dannie Durand (durand@cs.cmu.edu).