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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.
Grading
The exercise grade accounts for 60% of the final lecture grade. The grading will be based on your short 5 minutes bi-weekly presentation of your progress during the coding phase, 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:
- Tatyana Goldberg - a PhD student at RostLab and a former org admin and mentor of a JavaScript project in the Google Summer of Code (GSoC) Program
- Juan Miquel Cejuela - a PhD student at RostLab, text mining expert and functional programming languages enthusiast. Also creator of tagtog.net
Our exercises will heavily benefit from the expertise and enthusiasm of:
- Sebastian Wilzbach - a former GSoC student
- David Dao - another awesome Computer Scientist dude and also a former student of [1]
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) & HTML | Exercise 1 - Introduction |
23 Oct | Technology Fundamentals (HTML, CSS, SVG, Git(Hub), JS) | |
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 to BioJS |
Contact
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.
Recommended Readings
D3 - Interactive Data Visualization for the Web, Scott Murray, O’Reilly (2013) Free online version
Resources
- Git Guide, Tutorial, Reference, official website
- JavaScript
- Mozilla
- HTML5rocks
- Google JavaScript Style Guide
- Functional JS Garden
- NPM style guide
- Principles of Writing Consistent, Idiomatic JavaScript
- Advanced JS
- Codecademy JS
- Codeschool
- HTML & CSS