Exercise 'Protein Prediction II' for Computer Scientists
Welcome to our main information exchange for the exercise 'Protein Prediction II' for Computer Scientists!
The organization, requirements and grading of the exercise are explained here by the mentors. All students will have one log in account and may add content to this wiki, if required by the mentors.
The exercise grade accounts for 60% of the final lecture grade. The grading will be based on your short 5 minutes weekly (sometimes bi-weekly) presentation of your progress, the resulted visualization component that you will develop during the exercise, its clear and complete documentation, and the final 10 minutes presentation of the component to the group including Prof. Rost.
The mentors for the exercises will be:
- Juan Miquel Cejuela - a PhD student at RostLab, who is...
Our exercises will heavily benefit from the expertise and enthusiasm of:
- Sebastian Wilzbach - an awesome BioInfo dude and a former student of 
- David Dao - another awesome Computer Scientist dude and also a former student of 
One of the biggest breakthroughs in life sciences has been the ability to sequence the genetic code of life - the DNA. As the sequencing techniques become cheaper and faster, the amount of biological data stored in our databases is increasing every day. The data does not come from sequencing experiments only, but also from many other technologies that are used to understand organisms and diseases at the systems level. It a challenge nowadays to integrate the variety of data in a meaningful and research facilitating way.
Schedule & Notes
We encourage the students to retain from contacting the mentors by email. Instead please use the opportunity to talk to us during the exercise or use the PP2 CS 2014 mailing list. Feel free to post any question you might have concerning organizational or technical aspects of the exercise. The mentors will keep an eye on the mailing list but would expect (where possible) the students to help each other reciprocally.
D3 - Interactive Data Visualization for the Web, Scott Murray, O’Reilly (2013) Free online version
- Codecademy JS
- HTML & CSS