Modeling proteome networks with range-dependent graphs.
In this paper we consider the problem of characterizing and modeling large-scale protein-protein association networks using a class of range-dependent graphs which possess appropriate small world properties. These graphs may be employed in representing given association network using a maximum likelihood approach. This in turn annotates every observed association with its 'range', representing the tendency for such an association to be transitive. The application of a very rapidly developing field of graph theory to the emerging field of proetemics is novel and allows for a many-to-many relationship between individual proteins and groupings of proteins, which in turn may correspond to distinct functional behavior.
Grindrod
Peter
P
Numbercraft Limited, Magdalen Centre, The Oxford Science Park, Oxford, UK. peterg@numbercraft.co.uk
D008954:Models, Biological; D011506:Proteins / Q000145:classification / Q000502:physiology; D020543:Proteome / Q000145:classification* / Q000502:physiology*
D011506:Proteins; D020543:Proteome