Network Analysis In Biology
In this article, biologists use visual networks to help interpret the processes and interactions that go on inside a cell. The organisms in question is baker’s yeast, and the scientists are studying how the chromosome of the cell performs general “cell maintenance” and growth. By using a network analysis and visualization, the normally complex and hard to digest lists of protein relationships are displayed in a manner that provides insightful information to the scientists.
Let’s look at an example, and see how it relates to what we are doing in class:
The scientists are studying protein relationships, much like we study personal or business relationships in class, so they make the proteins their nodes. Similarly, the edges are interactions between proteins. That is what image “a” represents, for image “b”, they filtered the data more to gain a more usable network. First, they grouped the proteins according to their physical location in the cell, much like we could group Facebook friends by school or town. They then used a strategy we use by making the bold edges represent stronger interaction. Although not discussed for this image, it is interesting to think about the triadic closure principle here. One can observe that many of the clusters of protein nodes which have bold edges are well triangulated (top right yellow region, and bottom right red region), while others are not (Top left blue and middle left yellow).
The authors go on to discuss the various analysis methods that yield promising results, however, in the conclusion they caution future scientists (and this can be applied to all network users) to be careful of using networks on dynamic systems. They remind the readers that networks are two dimensional and can lead to a misrepresentation of relationships when taken out of context. Their example was a biochemical process that has wildly varying reactions and concentrations over time. This note was particularly useful as it has not yet been discussed in class, and brings in another dimension of understanding to the proper use of networks and network analysis.
http://www.nature.com/nbt/journal/v27/n10/full/nbt.1567.html