Alessia Annibale

Extensive parallel processing on scale-free networks.

Peter Sollich, Daniele Tantari, Alessia Annibale, 4 and Adriano Barra Department of Mathematics, King’s College London, Strand, London WC2R 2LS, U.K. Dipartimento di Matematica, Sapienza Università di Roma, P.le Aldo Moro 2, 00185, Roma, Italy. Institute for Mathematical and Molecular Biomedicine, King’s College London, Hodking Building, London SE1 1UL, U.K. Mathematics Department, King’s College London, The Strand WC2R 2LS, London, UK. Dipartimento di Fisica, Sapienza Università di Roma, P.le A. Moro 2, 00185, Roma, Italy. (Dated: April 15, 2014)

Immune networks: multitasking capabilities near saturation

Pattern-diluted associative networks were introduced recently as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with

Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods

N_T

Constrained Markovian Dynamics of Random Graphs

T-lymphocytes can manage a number

Tailored graph ensembles as proxies or null models for real networks I: tools for quantifying structure

N_B!=!\order(N_T^\delta)

Immune networks: multi-tasking capabilities at medium load

of B-lymphocytes simultaneously, with

What you see is not what you get: how sampling affects macroscopic features of biological networks

\delta!<!1

Bridging topological and functional information in protein interaction networks by short loops profiling

. Here we study this model in the extensive load regime

Spin, bond and global fluctuation–dissipation relations in the non-equilibrium spherical ferromagnet

N_B!=!\alpha N_T

Supersymmetric complexity in the Sherrington-Kirkpatrick model.

, with also a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivity regime, where each T-lymphocyte interacts with a finite number of B-lymphocytes as