@article {2015,
	title = {The phototransduction machinery in the rod outer segment has a strong efficacy gradient},
	number = {Proceedings of the National Academy of Sciences of the United States of America;Volume 112, issue 20; pp. E2715-E2724},
	year = {2015},
	note = {Open Access article},
	publisher = {National Academy of Sciences},
	doi = {10.1073/pnas.1423162112},
	url = {http://urania.sissa.it/xmlui/handle/1963/35157},
	author = {Monica Mazzolini and Giuseppe Facchetti and L. Andolfi and R. Proietti Zaccaria and S. Tuccio and J. Treud and Claudio Altafini and Enzo M. Di Fabrizio and Marco Lazzarino and G. Rapp and Vincent Torre}
}
@article {2013,
	title = {Common dynamical features of sensory adaptation in photoreceptors and olfactory sensory neurons.},
	journal = {Nature. Scientific Reports 3, Article number: 1251, Published  : 13 February 2013},
	year = {2013},
	publisher = {SISSA},
	abstract = {<p>Sensory systems adapt, i.e., they adjust their sensitivity to external stimuli according to the ambient level. In this paper we show that single cell electrophysiological responses of vertebrate olfactory receptors and of photoreceptors to different input protocols exhibit several common features related to adaptation, and that these features can be used to investigate the dynamical structure of the feedback regulation responsible for the adaptation. In particular, we point out that two different forms of adaptation can be observed, in response to steps and to pairs of pulses. These two forms of adaptation appear to be in a dynamical trade-off: the more adaptation to a step is close to perfect, the slower is the recovery in adaptation to pulse pairs and viceversa. Neither of the two forms is explained by the dynamical models currently used to describe adaptation, such as the integral feedback model.</p>},
	doi = {10.1038/srep01251},
	author = {Giovanna De Palo and Giuseppe Facchetti and Monica Mazzolini and Anna Menini and Vincent Torre and Claudio Altafini}
}
@article {2012,
	title = {Exploring the low-energy landscape of large-scale signed social networks},
	journal = {Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. Volume 86, Issue 3, 26 September 2012, Article number036116},
	year = {2012},
	publisher = {SISSA},
	abstract = {Analogously to a spin glass, a large-scale signed social network is characterized by the presence of disorder, expressed in this context (and in the social network literature) by the concept of structural balance. If, as we have recently shown, the signed social networks currently available have a limited amount of true disorder (or frustration), it is also interesting to investigate how this frustration is organized, by exploring the landscape of near-optimal structural balance. What we obtain in this paper is that while one of the networks analyzed shows a unique valley of minima, and a funneled landscape that gradually and smoothly worsens as we move away from the optimum, another network shows instead several distinct valleys of optimal or near-optimal structural balance, separated by energy barriers determined by internally balanced subcommunities of users, a phenomenon similar to the replica-symmetry breaking of spin glasses. Multiple, essentially isoenergetic, arrangements of these communities are possible. Passing from one valley to another requires one to destroy the internal arrangement of these balanced subcommunities and then to reform it again. It is essentially this process of breaking the internal balance of the subcommunities which gives rise to the energy barriers.},
	doi = {10.1103/PhysRevE.86.036116},
	url = {http://hdl.handle.net/1963/6504},
	author = {Giuseppe Facchetti and Giovanni Iacono and Claudio Altafini}
}
@article {2012,
	title = {Predicting and characterizing selective multiple drug treatments for metabolic diseases and cancer.},
	journal = {BMC Systems Biology. 29 August 2012, Page 115},
	year = {2012},
	publisher = {BioMed Central},
	abstract = {Background: In the field of drug discovery, assessing the potential of multidrug therapies is a difficult task because of the combinatorial complexity (both theoretical and experimental) and because of the requirements on the selectivity of the therapy. To cope with this problem, we have developed a novel method for the systematic in silico investigation of synergistic effects of currently available drugs on genome-scale metabolic networks. The algorithm finds the optimal combination of drugs which guarantees the inhibition of an objective function, while minimizing the side effect on the overall network. Results: Two different applications are considered: finding drug synergisms for human metabolic diseases (like diabetes, obesity and hypertension) and finding antitumoral drug combinations with minimal side effect on the normal human metabolism.The results we obtain are consistent with some of the available therapeutic indications and predict some new multiple drug treatments.A cluster analysis on all possible interactions among the currently available drugs indicates a limited variety on the metabolic targets for the approved drugs. Conclusion: The in silico prediction of drug synergism can represent an important tool for the repurposing of drug in a realistic perspective which considers also the selectivty of the therapy. Moreover, for a more profitable exploitation of drug-drug interactions, also drugs which show a too low efficacy but which have a non-common mechanism of action, can be reconsider as potential ingredients of new multicompound therapeutic indications.Needless to say the clues provided by a computational study like ours need in any case to be thoroughly evaluated experimentally.},
	doi = {doi:10.1186/1752-0509-6-115},
	url = {http://hdl.handle.net/1963/6515},
	author = {Giuseppe Facchetti and Claudio Altafini and Mattia Zampieri}
}
@article {2011,
	title = {Computing global structural balance in large-scale signed social networks.},
	journal = {Proceedings of the National Academy of Sciences of the United States of America. Volume 108, Issue 52, 27 December 2011, Pages 20953-20958},
	number = {PMID:22167802;},
	year = {2011},
	note = {Free fulltext article in Pubmed Central},
	publisher = {National Academy of Sciences},
	abstract = {Structural balance theory affirms that signed social networks (i.e., graphs whose signed edges represent friendly/hostile interactions among individuals) tend to be organized so as to avoid conflictual situations, corresponding to cycles of negative parity. Using an algorithm for ground-state calculation in large-scale Ising spin glasses, in this paper we compute the global level of balance of very large online social networks and verify that currently available networks are indeed extremely balanced. This property is explainable in terms of the high degree of skewness of the sign distributions on the nodes of the graph. In particular, individuals linked by a large majority of negative edges create mostly \\\"apparent disorder,\\\" rather than true \\\"frustration.\\\"},
	keywords = {Combinatorial optimization},
	doi = {10.1073/pnas.1109521108},
	url = {http://hdl.handle.net/1963/6426},
	author = {Giuseppe Facchetti and Giovanni Iacono and Claudio Altafini}
}
