Network Biology 2.0 part 3

The next speaker was Michael Cusick who talked about interactome networks and human diseases. He talked about basically doing yeast 2-hybrid studies crossing all proteins with all proteins. My mind still boggles at the scope of projects like this and I think it's incredible people do them. I find it interesting that they mention how their statisticians tell them they need something like ~10x coverage to fully recover the interactome but funding agencies seem to disagree. I think that these sorts of studies need the sort of tentpole funding that happened with the human genome project, the amount of funding they need is still an order of magnitude less than that and their resulting work is no less important it just doesn't have that sort of visceral appeal that the human genome project had to the public.

at first he only mentioned binary models which I took issue with but he seemed to indicate that they are moving towards a probabilistic model which is obviously the better choice.

He also spoke at length about literature curation and literature generated protein interaction networks, the literature of which I'm going to read in hopes of adapting it to genetic regulatory networks.

Lastly he talked about something called edgetics which is studying the phenotypic perturbations caused by removing a link between two proteins as opposed to knocking out a protein. He showed that edge perturbations gave rise to unique phenotypes which isn't so surprising, but I think it's fascinating that they were able to do this. I'm definitely going to be delving into these papers.

Robert weinberg then talked in great detail about cancer biology and morpohology which I frankly did not follow well at all, it seemed realy meaningful and his presentation and speaking was really great.

James Collins gave a talk on network biology and drug discovery. He stated that given inputs and outputs the network inside could be recreated, which isn't exactly true, some network that gives those outputs can be created but there are probably numerous equivalent networks that could create the same outputs from the given inputs.

He went on to discuss how synthetic biology could be used to perturb a cells regulatory states to learn the regulatory interaction network. However he did not elucidate what advantages this technique has over say knockdowns or knockout techniques (it may be more advantageous I just don't enough about it to say why).

He then went on to talk about how it seems likely that antibiotics that kill bacteria tend to do so by inducing the creation of hydroxyl radicals in their cells. This lead him to talk about how sub lethal levels of antibiotics didn't just not kill some bacteria but that they still induced hydroxyl radical formation which resulted in increased mutagenesis of the bacteria and increased resistance across antibiotics, scary!