E. Marinari

Institute for Biocomputation and Physics of Complex Systems, Caesaraugusta, Aragon, Spain

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Publications (251)617.89 Total impact

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    ABSTRACT: We use a sample-dependent analysis, based on medians and quantiles, to analyze the behavior of the overlap probability distribution of the Sherrington-Kirkpatrick and 3D Edwards-Anderson models of Ising spin glasses. We find that this approach is an effective tool to distinguish between RSB-like and droplet-like behavior of the spin-glass phase. Our results are in agreement with a RSB-like behavior for the 3D Edwards-Anderson model.
    06/2014;
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    ABSTRACT: We perform equilibrium parallel-tempering simulations of the 3D Ising Edwards-Anderson spin glass in a field. A traditional analysis shows no signs of a phase transition. Yet, we encounter dramatic fluctuations in the behaviour of the model: Averages over all the data only describe the behaviour of a small fraction of it. Therefore we develop a new approach to study the equilibrium behaviour of the system, by classifying the measurements as a function of a conditioning variate. We propose a finite-size scaling analysis based on the probability distribution function of the conditioning variate, which may accelerate the convergence to the thermodynamic limit. In this way, we find a non-trivial spectrum of behaviours, where a part of the measurements behaves as the average, while the majority of them shows signs of scale invariance. As a result, we can estimate the temperature interval where the phase transition in a field ought to lie, if it exists. Although this would-be critical regime is unreachable with present resources, the numerical challenge is finally well posed.
    Journal of Statistical Mechanics Theory and Experiment 03/2014; 2014(5). · 1.87 Impact Factor
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    ABSTRACT: We study the off-equilibrium dynamics of the three-dimensional Ising spin glass in the presence of an external magnetic field. We have performed simulations both at fixed temperature and with an annealing protocol. Thanks to the Janus special-purpose computer, based on field-programmable gate array (FPGAs), we have been able to reach times equivalent to 0.01 s in experiments. We have studied the system relaxation both for high and for low temperatures, clearly identifying a dynamical transition point. This dynamical temperature is strictly positive and depends on the external applied magnetic field. We discuss different possibilities for the underlying physics, which include a thermodynamical spin-glass transition, a mode-coupling crossover, or an interpretation reminiscent of the random first-order picture of structural glasses.
    Physical Review E 03/2014; 89(3-1):032140. · 2.31 Impact Factor
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    ABSTRACT: The observation that, through a titration mechanism, microRNAs (miRNAs) can act as mediators of effective interactions among their common targets (competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA hypothesis') that RNAs can regulate each other in extended 'cross-talk' networks. Such an ability might play a major role in post-transcriptional regulation (PTR) in shaping a cell's protein repertoire. Recent work focusing on the emergent properties of the cross-talk networks has emphasized the high flexibility and selectivity that may be achieved at stationarity. On the other hand, dynamical aspects, possibly crucial on the relevant time scales, are far less clear. We have carried out a dynamical study of the ceRNA hypothesis on a model of PTR. Sensitivity analysis shows that ceRNA cross-talk is dynamically extended, i.e. it may take place on time scales shorter than those required to achieve stationairity even in cases where no cross-talk occurs in the steady state, and is possibly amplified. Besides, in case of large, transfection-like perturbations the system may develop strongly non-linear, threshold response. Finally, we show that the ceRNA effect provides a very efficient way for a cell to achieve fast positive shifts in the level of a ceRNA when necessary. These results indicate that competition for miRNAs may indeed provide an elementary mechanism to achieve system-level regulatory effects on the transcriptome over physiologically relevant time scales.
    12/2013;
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    ABSTRACT: Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail) to eliminate them. As test cases, we tackle (a) the problem of identifying infeasible cycles in the E. coli metabolic network and (b) the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type specific metabolic networks. Results for (a) are compared with previous analyses of the same issue, while results for (b) are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method on one hand outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.
    Metabolites. 10/2013; 3(4).
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    ABSTRACT: The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity. We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (Vcyc) explains part of the uncoupling between glucose and oxygen utilization at increasing Vcyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by Vcyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of Vcyc. These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange.
    BMC Systems Biology 10/2013; 7(1):103. · 2.98 Impact Factor
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    ABSTRACT: We report a high-precision finite-size scaling study of the critical behavior of the three-dimensional Ising Edwards-Anderson model (the Ising spin glass). We have thermalized lattices up to L=40 using the Janus dedicated computer. Our analysis takes into account leading-order corrections to scaling. We obtain Tc = 1.1019(29) for the critical temperature, \nu = 2.562(42) for the thermal exponent, \eta = -0.3900(36) for the anomalous dimension and \omega = 1.12(10) for the exponent of the leading corrections to scaling. Standard (hyper)scaling relations yield \alpha = -5.69(13), \beta = 0.782(10) and \gamma = 6.13(11). We also compute several universal quantities at Tc.
    10/2013;
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    ABSTRACT: This paper describes the architecture, the development and the implementation of Janus II, a new generation application-driven number cruncher optimized for Monte Carlo simulations of spin systems (mainly spin glasses). This domain of computational physics is a recognized grand challenge of high-performance computing: the resources necessary to study in detail theoretical models that can make contact with experimental data are by far beyond those available using commodity computer systems. On the other hand, several specific features of the associated algorithms suggest that unconventional computer architectures, which can be implemented with available electronics technologies, may lead to order of magnitude increases in performance, reducing to acceptable values on human scales the time needed to carry out simulation campaigns that would take centuries on commercially available machines. Janus II is one such machine, recently developed and commissioned, that builds upon and improves on the successful JANUS machine, which has been used for physics since 2008 and is still in operation today. This paper describes in detail the motivations behind the project, the computational requirements, the architecture and the implementation of this new machine and compares its expected performances with those of currently available commercial systems.
    Computer Physics Communications 10/2013; 185(2). · 3.08 Impact Factor
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    ABSTRACT: A Comment on the Letter by B. Yucesoy, H. G. Katzgraber, and J. Machta, Phys. Rev. Lett. 109, 177204 (2012). The authors of the Letter offer a Reply.
    Physical Review Letters 05/2013; 110(21):219701. · 7.94 Impact Factor
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    ABSTRACT: It has recently been suggested that the competition for a finite pool of microRNAs (miRNA) gives rise to effective interactions among their common targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial for posttranscriptional regulation. We have studied a minimal model of posttranscriptional regulation where the emergence and the nature of such interactions can be characterized in detail at steady state. Sensitivity analysis shows that binding free energies and repression mechanisms are the key ingredients for the cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of repression values, can be symmetrical (one ceRNA influences another and vice versa) or asymmetrical (one ceRNA influences another but not the reverse), and may be highly selective, while possibly limited by noise. In addition, we show that nontrivial correlations among ceRNAs can emerge in experimental readouts due to transcriptional fluctuations even in the absence of miRNA-mediated cross-talk.
    Biophysical Journal 03/2013; 104(5):1203-13. · 3.67 Impact Factor
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    ABSTRACT: We describe Janus, an application-driven architecture for Monte Carlo simulations of spin glasses. Janus is a massively parallel architecture, based on reconfigurable FPGA nodes; it offers two orders of magnitude better performance than commodity systems for spin glass applications. The first generation Janus machine has been operational since early 2008; we are currently developing a new generation, that will be on line in early 2013. In this paper we present the Janus architecture, describe both implementations and compare their performances with those of commodity systems.
    Proceedings of the 18th international conference on Parallel processing workshops; 08/2012
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    ABSTRACT: The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample (10(6)) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.
    PLoS Computational Biology 06/2012; 8(6):e1002562. · 4.87 Impact Factor
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    ABSTRACT: We review recent work on the statistical mechanics of Von Neumann's growth model and discuss its application to cellular metabolic networks. In this context, we present a detailed analysis of the physiological scenario underlying optimality a la Von Neumann in the metabolism of the bacterium Escherichia coli, showing that optimal solutions are characterized by a considerable microscopic flexibility accompanied by a robust emergent picture for the key physiological functions. This suggests that the ideas behind optimal economic growth in Von Neumann's model can be helpful in uncovering functional organization principles of cell energetics.
    The European Physical Journal Special Topics 05/2012; 212(1). · 1.80 Impact Factor
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    A. Billoire, A. Maiorano, E. Marinari
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    ABSTRACT: We study the 3D Edwards-Anderson spin glasses, by analyzing spin-spin correlation functions in thermalized spin configurations at low T on large lattices. We consider individual disorder samples and analyze connected clusters of very correlated sites: we analyze how the volume and the surface of these clusters increases with the lattice size. We qualify the important excitations of the system by checking how large they are, and we define a correlation length by measuring their gyration radius. We find that the clusters have a very dense interface, compatible with being space filling.
    Journal of Statistical Mechanics Theory and Experiment 05/2012; 2012(12). · 1.87 Impact Factor
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    ABSTRACT: We describe Janus, a massively parallel FPGA-based computer optimized for the simulation of spin glasses, theoretical models for the behavior of glassy materials. FPGAs (as compared to GPUs or many-core processors) provide a complementary approach to massively parallel computing. In particular, our model problem is formulated in terms of binary variables, and floating-point operations can be (almost) completely avoided. The FPGA architecture allows us to run many independent threads with almost no latencies in memory access, thus updating up to 1024 spins per cycle. We describe Janus in detail and we summarize the physics results obtained in four years of operation of this machine; we discuss two types of physics applications: long simulations on very large systems (which try to mimic and provide understanding about the experimental non-equilibrium dynamics), and low-temperature equilibrium simulations using an artificial parallel tempering dynamics. The time scale of our non-equilibrium simulations spans eleven orders of magnitude (from picoseconds to a tenth of a second). On the other hand, our equilibrium simulations are unprecedented both because of the low temperatures reached and for the large systems that we have brought to equilibrium. A finite-time scaling ansatz emerges from the detailed comparison of the two sets of simulations. Janus has made it possible to perform spin-glass simulations that would take several decades on more conventional architectures. The paper ends with an assessment of the potential of possible future versions of the Janus architecture, based on state-of-the-art technology.
    The European Physical Journal Special Topics 04/2012; 210(1). · 1.80 Impact Factor
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    ABSTRACT: Spin glasses are a longstanding model for the sluggish dynamics that appears at the glass transition. However, spin glasses differ from structural glasses for a crucial feature: they enjoy a time reversal symmetry. This symmetry can be broken by applying an external magnetic field, but embarrassingly little is known about the critical behaviour of a spin glass in a field. In this context, the space dimension is crucial. Simulations are easier to interpret in a large number of dimensions, but one must work below the upper critical dimension (i.e., in d<6) in order for results to have relevance for experiments. Here we show conclusive evidence for the presence of a phase transition in a four-dimensional spin glass in a field. Two ingredients were crucial for this achievement: massive numerical simulations were carried out on the Janus special-purpose computer, and a new and powerful finite-size scaling method.
    Proceedings of the National Academy of Sciences 02/2012; 109(17). · 9.74 Impact Factor
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    ABSTRACT: Using the results of large scale numerical simulations we study the probability distribution of the pseudo critical temperature for the three-dimensional Edwards-Anderson Ising spin glass and for the fully connected Sherrington-Kirkpatrick model. We find that the behavior of our data is nicely described by straightforward finite-size scaling relations.
    Journal of Statistical Mechanics Theory and Experiment 08/2011; 2011(10). · 1.87 Impact Factor
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    ABSTRACT: We study the sample-to-sample fluctuations of the overlap probability densities from large-scale equilibrium simulations of the three-dimensional Edwards-Anderson spin glass below the critical temperature. Ultrametricity, Stochastic Stability and Overlap Equivalence impose constraints on the moments of the overlap probability densities that can be tested against numerical data. We found small deviations from the Ghirlanda-Guerra predictions, which get smaller as system size increases. We also focus on the shape of the overlap distribution, comparing the numerical data to a mean-field-like prediction in which finite-size effects are taken into account by substituting delta functions with broad peaks
    Physical review. B, Condensed matter 07/2011; · 3.77 Impact Factor
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    ABSTRACT: The analysis of non-equilibrium steady states of biochemical reaction networks relies on finding the configurations of fluxes and chemical potentials satisfying stoichiometric (mass balance) and thermodynamic (energy balance) constraints. Efficient methods to explore such states are crucial to predict reaction directionality, calculate physiologic ranges of variability, estimate correlations, and reconstruct the overall energy balance of the network from the underlying molecular processes. While different techniques for sampling the space generated by mass balance constraints are currently available, thermodynamics is generically harder to incorporate. Here we introduce a method to sample the free energy landscape of a reaction network at steady state. In its most general form, it allows to calculate distributions of fluxes and concentrations starting from trial functions that may contain prior biochemical information. We apply our method to the human red blood cell's metabolic network, whose space of mass-balanced flux states has been sampled extensively in recent years. Specifically, we profile its thermodynamically feasible flux configurations, characterizing in detail how fluctuations of fluxes and potentials are correlated. Based on this, we derive the cell's energy balance in terms of entropy production, chemical work done and thermodynamic efficiency.
    07/2011;

Publication Stats

5k Citations
617.89 Total Impact Points

Institutions

  • 2005–2014
    • Institute for Biocomputation and Physics of Complex Systems
      Caesaraugusta, Aragon, Spain
  • 2013
    • Italian Institute of Technology (IIT)
      Genova, Liguria, Italy
  • 2000–2012
    • Sapienza University of Rome
      • Department of Physics
      Roma, Latium, Italy
    • Complutense University of Madrid
      • Department of Theoretical physics I
      Madrid, Madrid, Spain
  • 2010
    • Universidad de Extremadura
      • Department of Electric Engineering, Electronics and Automatics
      Ara Pacis Augustalis, Extremadura, Spain
    • University of Zaragoza
      • Department of Theoretical Physics
      Caesaraugusta, Aragon, Spain
  • 2008
    • Universita degli studi di Ferrara
      • Department of Physics and Earth Sciences
      Ferrara, Emilia-Romagna, Italy
  • 1994–2007
    • Università degli studi di Cagliari
      • Department of Physics
      Cagliari, Sardinia, Italy
  • 1992–2007
    • Syracuse University
      • Department of Physics
      Syracuse, NY, United States
  • 1982–2007
    • University of Rome Tor Vergata
      • Dipartimento di Fisica
      Roma, Latium, Italy
  • 1998–2006
    • Università Degli Studi Roma Tre
      • Department of Mathematics and Physics
      Roma, Latium, Italy
    • Universidade Federal de Viçosa (UFV)
      • Departamento de Física
      Viçosa, Minas Gerais, Brazil
  • 2001
    • Université Paris-Sud 11
      • Laboratoire de Physique Théorique et Modèles Statistiques
      Paris, Ile-de-France, France
  • 1981–1988
    • INFN - Istituto Nazionale di Fisica Nucleare
      Frascati, Latium, Italy
    • CERN
      Genève, Geneva, Switzerland
  • 1987
    • The Rockefeller University
      New York City, New York, United States
  • 1986
    • École Polytechnique
      Paliseau, Île-de-France, France
  • 1982–1986
    • Università degli Studi Europea di Roma
      Roma, Latium, Italy
  • 1983
    • Brookhaven National Laboratory
      New York City, New York, United States
  • 1981–1982
    • Università degli Studi del Sannio
      Benevento, Campania, Italy