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2012
Dall'Asta L, Marsili M, Pin P. Collaboration in social networks. Proceedings of the National Academy of Sciences. 2012;109:4395-400. Abstract
Gaonkar KS, Gulati G, Balu K, Purohit R. Computational evaluation of small molecule inhibitors of RGS4 to regulate the dopaminergic control of striatal LTD. Egyptian Journal of Medical Human Genetics. 2012:-.
Alemi-Neissi A, Baldassi C, Braunstein A, Pagnani A, Zecchina R, Zoccolan D. Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition. BMC Neuroscience. 2012;13:1-2.
2011
Bailly-Bechet M, Benecke A, Hardt WD, Lanza V, Sturm A, Zecchina R. An externally modulated, noise-driven switch for the regulation of SPI1 in Salmonella enterica serovar Typhimurium. Journal of Mathematical Biology. 2011;63:637-62.
Dall'Asta L, Pin P, Ramezanpour A. Optimal equilibria of the best shot game. Journal of Public Economic Theory. 2011;13(6).
Ramezanpour A, Realpe J, Zecchina R. Statistical physics approach to graphical games: local and global interactions. Eur. Phys. J. B. 2011;81(3).
2009
Baldassi C. Generalization Learning in a Perceptron with Binary Synapses. Journal of Statistical Physics. 2009;136(5). Abstract  Download: Baldassi09.pdf (562.66 KB)
Bailly-Bechet M, Braunstein A, Zecchina R. A Prize-Collecting Steiner Tree Approach for Transduction Network Inference. In: Proceedings of the 7th International Conference on Computational Methods in Systems Biology. Springer; 2009. 95.
2008
Braunstein A, Mulet R, Pagnani A. Estimating the size of the solution space of metabolic networks. BMC Bioinformatics. 2008;9:240. Abstract
Braunstein A, Pagnani A, Weigt M, Zecchina R. Inference algorithms for gene networks: a statistical mechanics analysis. Journal of Statistical Mechanics: Theory and Experiment. 2008;2008:P12001 (29pp). Abstract
Lanza V, Corinto F, Gilli M. On the study of cellular nonlinear networks via amplitude and phase dynamics. Neural Networks. 2008;21:122-9.
Bayati M, Braunstein A, Zecchina R. A rigorous analysis of the cavity equations for the minimum spanning tree. Journal of Mathematical Physics. 2008;49:125206. Download: BaBrZe2008.pdf: Copyright (2008) American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. (270.23 KB)
Bayati M, Borgs C, Braunstein A, Chayes J, Ramezanpour A, Zecchina R. Statistical Mechanics of Steiner Trees. Physical Review Letters. 2008;101:37208. Abstract  Download: prl-steiner.pdf (210.2 KB)
2007
Lanza V, Corinto F, Gilli M. Analysis of nonlinear oscillatory network dynamics, via time-varying amplitude and phase variables. International Journal of Circuit Theory and Applications. 2007;35:623-44.
Baldassi C, Braunstein A, Brunel N, Zecchina R. Efficient supervised learning in networks with binary synapses. Proceedings of the National Academy of Sciences. 2007;104:11079-84.
Baldassi C, Braunstein A, Brunel N, Zecchina R. Efficient supervised learning in networks with binary synapses. Proceedings of the National Academy of Sciences. 2007;104:11079-84.
Mahmoudi H, Pagnani A, Weigt M, Zecchina R. Propagation of external regulation and asynchronous dynamics in random Boolean networks. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2007;17:026109.
Ramezanpour A. Intermittent exploration on a scale-free network. EPL. 2007;77:60004.
2006
Correale L, Leone M, Pagnani A, Weigt M, Zecchina R. The computational core and fixed point organization in Boolean networks. Journal of Statistical Mechanics: Theory and Experiment. 2006;3:P03002.
Correale L, Leone M, Pagnani A, Weigt M, Zecchina R. Core Percolation and Onset of Complexity in Boolean Networks. Physical Review Letters. 2006;96:18101.
Lanza V, Ambrosi D, Preziosi L. Exogenous control of vascular network formation in vitro: a mathematical model. NETWORKS AND HETEROGENEOUS MEDIA. 2006;1:621.
Braunstein A, Zecchina R. Learning by message-passing in networks of discrete synapses. Phys. Rev. Lett.. 2006;96:030201. Download: prl-synapses.pdf (233.04 KB)
2005
Chavas J, Battaglia D, Ciccutin A, Zecchina R. Construction and VHDL implementation of a fully local network with good reconstruction properties of the inputs. Artificial Intelligence and Knowledge Engineering Applications: a Bioinspired approach, J. Mira, JR Alvarez editors, Part II. 2005:385-94.
Ramezanpour A, Vaez Allaei SM. Elastic properties of small-world spring networks. Physical Review E. 2005;72:66115.
2004
Ramezanpour A. Biology helps to construct weighted scale-free networks. Europhysics Letters. 2004;68:316-22.