Michael Bell

As documented in numerous posts, a key aspect of my research has been the application of power laws to word occurrence in bulk biological annotation. A large portion of this work has recently been accepted at the European Conference on Computational Biology (ECCB) 2012 and the resulting paper will shortly appear in a special issue of Bioinformatics. The acceptance into ECCB’12 requires an oral presentation. Therefore, I am currently in the process of creating a selection of images and slides for this talk.

As is clear from previous posts, this work produces a lot of graphs. One of the challenges of writing the paper was trying to include figures that allow the key points to be clearly made within the page limit enforced upon us. For example, if we show the resulting graph for all versions of Swiss-Prot, TrEMBL and the overlay of both we will comfortably exceed 100 images. This clearly cannot be suitably done in publication format, nor will the resulting paper clearly show the change over time (Well, I guess we could have produced something along the lines of a “flick book” as part of the publication – however, I’m unsure my supervisor would be happy with the subsequent publication and colour figure costs that OUP would charge)

However, unlike the paper, the presentation provides an ideal opportunity to show these graphs and the change over time. To do this I have created animated images for Swiss-Prot, TrEMBL and overlay images. The animations run reasonably quickly – 1/10th of a second between transitions. I have provided two further links for each of the animations which are slower (50ms and 1 second between transitions) below each graph. These graphs are shown below:

Make it slower or even slower still…

Make it slower or even slower still…

Make it slower or even slower still…

These views clearly show, for example, the divergence between Swiss-Prot and TrEMBL over time. These animations are a powerful way to visually analyse data that cannot be replicated by viewing static images side by side, or the extracted alpha values. For example, viewing the change in Swiss-Prot over time we see that while the head of the power law is “structurally” similar, it actually drops significantly (from the second point, i.e. x = 2) over time. This would suggest that over time the richness of individual words appears to be increasing — i.e. more words are occurring only a single time in later versions.

However, I’m not convinced that the animation of word clouds is quite as meaningful:

These word clouds show the various words in Swiss-Prot annotations over time. I have previously blogged about these as well making all the images available on my website.