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We apply our recently developed information-theoretic measures for the characterisation and comparison of protein-protein interaction networks. These measures are used to quantify topological network features via macroscopic statistical properties. Network differences are assessed based on these macroscopic properties as opposed to microscopic overlap,(More)
The entropy of a hierarchical network topology in an ensemble of sparse random networks, with "hidden variables" associated with its nodes, is the log-likelihood that a given network topology is present in the chosen ensemble. We obtain a general formula for this entropy, which has a clear interpretation in some simple limiting cases. The results provide(More)
Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30(More)
Herein we discuss how FRET imaging can contribute at various stages to delineate the function of the proteome. Therefore, we briefly describe FRET imaging techniques, the selection of suitable FRET pairs and potential caveats. Furthermore, we discuss state-of-the-art FRET-based screening approaches (underpinned by protein interaction network analysis using(More)
The Rho GTPase Cdc42 regulates cytoskeletal changes at the immunological synapse (IS) that are critical to T-cell activation. By imaging fluorescent activity biosensors (Raichu) using fluorescence lifetime imaging microscopy, Cdc42 activation was shown to display kinetics that are conditional on the specific receptor input (through two IS-associated(More)
Genomics and proteomics will improve outcome prediction in cancer and have great potential to help in the discovery of unknown mechanisms of metastasis, ripe for therapeutic exploitation. Current methods of prognosis estimation rely on clinical data, anatomical staging and histopathological features. It is hoped that translational genomic and proteomic(More)
Breast cancer heterogeneity demands that prognostic models must be biologically driven and recent clinical evidence indicates that future prognostic signatures need evaluation in the context of early compared with late metastatic risk prediction. In pre-clinical studies, we and others have shown that various protein-protein interactions, pertaining to the(More)
A simple model of coupled dynamics of fast neurons and slow interactions , modelling self-organization in recurrent neural networks, leads naturally to an effective statistical mechanics characterized by a partition function which is an average over a replicated system. This is reminiscent of the replica trick used to study spin-glasses, but with the(More)
We generate new mathematical tools with which to quantify the macroscopic topological structure of large directed networks. This is achieved via a statistical mechanical analysis of constrained maximum entropy ensembles of directed random graphs with prescribed joint distributions for in-and out-degrees and prescribed degree–degree correlation functions. We(More)