I use a five star rating about how useful I found the talk but remember that is always personal!
Systems Biology Graphical Notation
Nicolas de la Novere **
SBGN is a support for creating views of networks as there are many different possible representations and a useful tool cannot constrain the representation you wish to create.
Rule-based modelling: Model perturbations and resolution
Russell Harmer *****
Excellent simple technique for creating rules based agent models that only depends on defining the entities and the relationships between them. This allows many species to be grouped and simplified and prevents a combinatorial explosion. The use of hierarchies of agents removes the problem of a second combinatorial explosion when you are trying to deal with mutations and modified species. It is simple to adapt as a verbal model and there is none of the maths of ODEs but it gives a useful representation that improves our knowledge. This demonstrates that verbal models are still important in biology and that maths still has limitations where there is complexity.
Topological network alignment uncovers biological function and phylogeny
Tijana Milenkovic ***
A breathless talk but it kept me awake. The aim of the work is to use network topology to discover biological features without using sequence information. Currently methods align the sequences at nodes and when they are homologous they align them and do not only depend on network topology. This includes a heuristic to compare networks which is a nice problem to work on in itself. If you have a metric for the distances between networks then you can construct phylogentic trees.
The heuristc starts from a seed node that is aligned between the two networks based on the graphlet degree vector of that node i.e. how many triangles and rhomboids are found centred on that node. The ultimate finding is that the phylogeny using the topological alignment distance agrees with that from sequence methods in funghi and protists.
Question: asked about how the metabolic networks of the funghi were reconstructed and this uses sequence homology and so there is an indirect element of sequence homology in the networks that are being compared. This question brought a laugh from the audience by saying this is why the tree based on sequence homology is the same as that from the new program.
But this is wrong the phylogentic tree based on sequence is likely to be based on rRNA and not amino acids, as phylogeny is different for different genes and so you would get a different phylogeny for different parts of the network!
The possible weakness of the work is that adding the sequence removes the degeneracy problem to make sure you have aligned the right nodes in the two networks to each other. Then from these "seeds" you can extend it to align nodes where there is little sequence identity that might suggest duplication and recruitment events. Never forget the biology.