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From Protein Prediction 2 Winter Semester 2014
Revision as of 18:38, 10 October 2014 by Goldberg (talk | contribs) (Mentors)

Exercise 'Protein Prediction II' for Computer Scientists

This is the main information exchange for the exercise 'Protein Prediction II' for Computer Scientists. The organisation, requirements and grading of the exercise is 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.

Grading

The exercise grade accounts for 60% of the final lecture grade. The grading will be based on your active participation in the exercises, as well as on the visualization component you will develop during the exercise, its clear and complete documentation, and the final presentation of the component to the group including Prof. Rost.

Mentors

The mentors for the exercises will be:

Our exercises will heavily benefit from the expertise and enthusiasm of:

  • Sebastian Wilzbach - an awesome BioiInfo dude and a former student of [GSoC]
  • David Dao - another awesome Computer Scientist dude and also a former student of [GSoC] ;))))

Project description

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 meaningful and research facilitating way.

The visualization plays a crucial role in the ability of interpreting the data and focusing on those details that shed light on specific hypotheses. The complexity of the data we are facing in modern life sciences requires more advances technologies than the usual static HTML pages when accessing them. They require dynamic visualization tools that allow real-time interactions. JavaScript is a language of modern browsers and thus is perfect for developing client-side browser-based tools. In the exercises of this semester we will build tools for the visualization of biological data on the web from scratch and share those with the community!

Exercise Oct 16, 2014

In the first exercise we will give you an introduction to the programming language of the web - JavaScript. We will also talk about BioJS, whose library we aim to enhance by the awesome components that will outcome by the end of this semester's exercise.

[Slides]

TODO list for next week:

  • todo1
  • todo2
  • todo3

After completing the [BioJS tutorial], please rate the difficulty of the tutorial on a scale from 1 (very easy) to 5 (very hard) in the table below. The rating will be done anonymously and its purpose is for us to understand the level of your JavaScript knowledge to best tailor the upcoming exercises for you.

student 1 student 2 student 3 student 4 student 5 student 6 student 7 student 8 student 9 student 10
student 11 student 12 student 13 student 14 student 15 student 16 student 17 student 18 student 19 student 20