title: Review of uses of network and graph theory concepts within proteomics.
abstract: The size and nature of data collected on gene and protein interactions has led to a rapid growth of interest in graph theory and modern techniques for describing, characterizing and comparing networks. Simultaneously, this is a field of growth within mathematics and theoretical physics, where the global properties, and emergent behavior of networks, as a function of the local properties has long been studied. In this review, a number of approaches for exploiting modern network theory to help describe and analyze different data sets and problems associated with proteomic data are considered. This review aims to help biologists find their way towards useful ideas and references, yet may also help scientists from a mathematics and physics background to understand where they may apply their expertise.
authors.affiliation: Magadalen Centre, Lawson Software, The Oxford Science Park, Oxford OX4 4GA, UK. peter.grindrod@lawson.com
authors.forename: Peter
authors.initials: P
authors.lastname: Grindrod
authors.forename: Milla
authors.initials: M
authors.lastname: Kibble
mesh_terms: D008962:Models, Theoretical; D009415:Nerve Net; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D040901:Proteomics / Q000379:methods*
chemical_list: D011506:Proteins