title: Role-similarity based functional prediction in networked systems: application to the yeast proteome.
abstract: We propose a general method to predict functions of vertices where (i) the wiring of the network is somehow related to the vertex functionality and (ii) a fraction of the vertices are functionally classified. The method is influenced by role-similarity measures of social network analysis. The two versions of our prediction scheme are tested on model networks where the functions of the vertices are designed to match their network surroundings. We also apply these methods to the proteome of the yeast Saccharomyces cerevisiae and find the results compatible with more specialized methods.
authors.affiliation: Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA. pholme@umich.edu
authors.forename: Petter
authors.initials: P
authors.lastname: Holme
authors.forename: Mikael
authors.initials: M
authors.lastname: Huss
mesh_terms: D000818:Animals; D003198:Computer Simulation; D015870:Gene Expression / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D011157:Population Dynamics; D020543:Proteome / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000502:physiology*; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins