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From Protein Prediction 2 Winter Semester 2014
Revision as of 10:37, 15 October 2014 by Goldberg (talk | contribs) (Mentors)

Exercise 'Protein Prediction II' for Computer Scientists

Protein Interaction Network, Phylogenetic Tree, Microarray Scatterplot

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.

Grading

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.

Mentors

(TG:TODO)

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 a 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!

Schedule & Notes

Date Topic Link
16 Oct Introduction to BioJS (Guest lecturer: Dr. Manuel Corpas) Exercise 1 - Introduction
23 Oct Technology Fundamentals (HTML, CSS, SVG, JavaScript)
30 Oct Introduction to D3 and Interactive Visualization
06 Nov Visualization Principles & Best Practice
13 Nov Project Proposals
20 Nov Supervised Team Meeting
03 Dec Supervised Team Meeting
17 Dec Supervised Team Meeting
08 Jan Final Project Presentation (Prof. Rost)
15 Jan Deadline for Documentation and Submission into BioJS

Recommended Readings

Scott.jpg

D3 - Interactive Data Visualization for the Web, Scott Murray, O’Reilly (2013) Free online version

Resources

JavaScript
HTML & CSS