IPython Notebook and de Bruijn Graph

IPython Notebook is an excellent tool for visualizing graphs. For introduction, please check this video from C. T. Brown.

Also, the following two tutorials from his student (disowned, see comment :)) are helpful - here and here.

We have not used it yet, but would like to get started soon. One big reason is a demo for de Bruijn graphs from Jason Chin, a talented physicist and bioinformatician, who also brings us an amazing variety of cool information through his Twitter feed infoecho. Did we mention that he also knows PacBio technology inside out?

Check out this if you are a IPython Notebook fan.

https://github.com/cschin/ipython_d3_mashup/blob/master/ipython_13_vis_example /De_Bruijn_VIS.ipynb

It used IPython Notebook + d3.js to get interactive visualization for de Bruijn Graphs

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P. S.

Jason Chin also asked this question -

Internet is a completely anarchic medium of exchange, and so we expect to see all types of Twitter feeds, ranging from ‘very chatty’ to ‘speak only’. That does not bother us, and the amazing thing about internet tools like Twitter is that they can bring such wide range of people together to communicate.

We are not ‘speak only’ in Twitter, but we are definitely among ‘follow few’ and here is why. We are trying to figure out how to use Twitter as our mini Haldane’s Sieve, and for that, we decided to follow few high-quality /high-volume feeds. The choices are arbitrary and purely subjective. We hope those feeds will retweet anything they find interesting, and save our work of trying to read every single paper.

We wanted to name the strategy nani gigantum humeris insidentes :)