Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Alfredo Braunstein"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Estimating observables from conditioned dynamics is typically computationally hard. While obtaining independent samples efficiently from unconditioned dynamics is usually feasible, most of them do not satisfy the imposed conditions and must
Externí odkaz:
https://doaj.org/article/3c7cc8ebb24242e0badfe41831a7aa3d
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract The reconstruction of missing information in epidemic spreading on contact networks can be essential in the prevention and containment strategies. The identification and warning of infectious but asymptomatic individuals (i.e., contact traci
Externí odkaz:
https://doaj.org/article/c1b6734d88bf445bb13558d835c27a8f
Publikováno v:
Nature Communications, Vol 8, Iss 1, Pp 1-9 (2017)
Large-scale metabolic models of organisms from microbes to mammals can provide great insight into cellular function, but their analysis remains challenging. Here, the authors provide an approximate analytic method to estimate the feasible solution sp
Externí odkaz:
https://doaj.org/article/a310c3829c1b4c4c9dfde675741de891
Publikováno v:
PLoS ONE, Vol 12, Iss 4, p e0176376 (2017)
The massive employment of computational models in network epidemiology calls for the development of improved inference methods for epidemic forecast. For simple compartment models, such as the Susceptible-Infected-Recovered model, Belief Propagation
Externí odkaz:
https://doaj.org/article/61de639eeb39440d9b8bced5608f14a3
Publikováno v:
PLoS ONE, Vol 10, Iss 7, p e0119286 (2015)
We study a class of games which models the competition among agents to access some service provided by distributed service units and which exhibits congestion and frustration phenomena when service units have limited capacity. We propose a technique,
Externí odkaz:
https://doaj.org/article/000f0650d952476493b08d2412f7225d
Publikováno v:
PLoS ONE, Vol 10, Iss 12, p e0145222 (2015)
We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by inc
Externí odkaz:
https://doaj.org/article/97c56a1b3a6a4a70995d92c6e7537fc5
Autor:
Evan J Molinelli, Anil Korkut, Weiqing Wang, Martin L Miller, Nicholas P Gauthier, Xiaohong Jing, Poorvi Kaushik, Qin He, Gordon Mills, David B Solit, Christine A Pratilas, Martin Weigt, Alfredo Braunstein, Andrea Pagnani, Riccardo Zecchina, Chris Sander
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 12, p e1003290 (2013)
We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic
Externí odkaz:
https://doaj.org/article/b42abf9d37ee45299b42ecb7866bb94f
Publikováno v:
Physical review. E. 106(5-1)
We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simple linear cost, measuring the Hamming distance with respect to a refere
Autor:
Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani, Daniele De Martino, Andrea De Martino
Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This remarkable robustness suggests that, at least in bacteria, metabolic act
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbb4427910865bb4da3ad0d262d621ac
http://hdl.handle.net/10261/296486
http://hdl.handle.net/10261/296486
Publikováno v:
Physical review. E. 103(4-1)
Efficient feature selection from high-dimensional datasets is a very important challenge in many data-driven fields of science and engineering. We introduce a statistical mechanics inspired strategy that addresses the problem of sparse feature select