@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 {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}
}
