title: Evolution of the cognitive proteome: from static to dynamic network models.
abstract: Integrative analysis of the neuronal synapse proteome has uncovered an evolutionarily conserved signalling complex that underpins the cognitive capabilities of the brain. Highly dynamic, cell type specific and intricately regulated, the synaptic proteome presents many challenges to systems biology approaches, yet this is likely to be the best route to unlock a new generation of neuroscience research and CNS drug development that society so urgently demands. Most systems biology approaches today have focussed on exploiting protein-protein interaction data to their fullest extent within static interaction models. These have revealed structure-function relationships within the protein network, uncovered new candidate genes for genetic studies and drug research and development and finally provided a means to study the evolution of the system. The rapid maturation of medium and high-throughput biochemical technologies means that dissecting the synapse proteome's dynamic complexity is fast becoming a reality. Here we look at these new challenges and explore rule-based modelling as a basis for a new generation of synaptic models.
authors.affiliation: School of Informatics, University of Edinburgh, Edinburgh, UK. douglas.armstrong@ed.ac.uk
authors.forename: J Douglas
authors.initials: JD
authors.lastname: Armstrong
authors.forename: Oksana
authors.initials: O
authors.lastname: Sorokina
mesh_terms: D000818:Animals; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000166:cytology / Q000378:metabolism; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods; D015398:Signal Transduction; D013569:Synapses / Q000378:metabolism*; D049490:Systems Biology / Q000379:methods
chemical_list: D020543:Proteome