The high-school hierarchy in protein networks

The building blocks of cells, proteins, interact and form networks (each node is a protein and each link an interaction between them) See also Sumeet's post. We think that biological systems are modular. A module is a section of a whole that carries out its function relatively independently of the rest of the system (for example, consider the various components of your PC). Candidates for modules in a network are communities, groups of proteins that interact very closely with each other, and not so much with the rest of the network. There are algorithms that exist that can detect such communities.

But maybe there are communities inside each community. If you consider the social interaction network of a school (where nodes are pupils and links are friendships between them), you might expect there to be several large communities, one for each of the year groups. But, if pupils are more likely to be friends not only with someone in their year, but also with someone in their class, then each one of these large year-group communities would consist of several smaller communities, one for each of the class groups. At a yet smaller scale, each of these class-group communities might contain several friendship-group communities. In other words, there is structure of interest at many scales within the network.

We set out to investigate the multi-scale community structure of protein interaction networks. You can see this structure visualised in the image. On the top line (log(lambda)=-1) we are looking at the network at a low resolution: all the nodes are considered to be in one (purple) community. Moving down the figure (e.g. log(lambda)=1) increases resolution (like paying attention to classrooms instead of the whole school) and more structure is resolved: this community starts to split into several large communities. As we crank up the resolution yet higher (further down the image), these communities themselves split up.

Why are we interested in this structure? Proteins within a community might be expected to all carry out a similar task. We were interested if this was true at all scales: the result varied depending on which groups of proteins we were looking at. We were also interested because we simply don't know anything about many proteins, but perhaps the communities they are members of can suggest functions for them. In the school analogy, if all you knew about a pupil was which communities they were a member of, you could make a pretty good guess at many things particular to them, e.g. who their teacher was, whether they'd be studying for exams.

You can read the full story in our paper "The Function of Communities in Protein Interaction Networks at Multiple Scales" in BMC Systems Biology 4, 100 (2010): here. You can also read more about this work in this short review in Biomedical Computational Review. Anna and Nick