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San Marco dei Cavoti, Italy

Lane D.A.,European Center for Living Technology | Lane D.A.,University of Modena and Reggio Emilia
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2016

Innovation cascades inextricably link the introduction of new artefacts, transformations in social organization, and the emergence of new functionalities and new needs. This paper describes a positive feedback dynamic, exaptive bootstrapping, through which these cascades proceed, and the characteristics of the relationships in which the new attributions that drive this dynamic are generated. It concludes by arguing that the exaptive bootstrapping dynamic is the principal driver of our current Innovation Society. © 2016 The Author(s) Published by the Royal Society. All rights reserved. Source


Slanzi D.,University of Venice | Poli I.,European Center for Living Technology
Chemometrics and Intelligent Laboratory Systems | Year: 2014

Laboratory experimentation is increasingly concerned with systems whose dynamical behaviour can be affected by a very large number of variables. Objectives of experimentation on such systems are generally both the optimisation of some experimental responses and efficiency of experimentation in terms of low investment of resources and low impact on the environment. Design and modelling for high dimensional systems with these objectives present hard and challenging problems, to which much current research is devoted. In this paper, we introduce a novel approach based on the evolutionary principle and Bayesian network models. This approach can discover optimum values while testing just a very limited number of experimental points. The very good performance of the approach is shown both in a simulation analysis and biochemical study concerning the emergence of new functional bio-entities. © 2014 Elsevier B.V. Source


Shaw R.S.,ProtoLife Inc. | Shaw R.S.,Max Planck Institute for Dynamics and Self-Organization | Packard N.H.,ProtoLife Inc. | Packard N.H.,European Center for Living Technology | Packard N.H.,Santa Fe Institute
Physical Review Letters | Year: 2010

A concentration difference of particles across a membrane perforated by pores will induce a diffusive flux. If the diffusing objects are of the same length scale as the pores, diffusion may not be simple; objects can move into the pore in a configuration that requires them to back up in order to continue forward. A configuration that blocks flow through the pore may be statistically preferred, an attracting metastable state of the system. This effect is purely kinetic, and not dependent on potentials, friction, or dissipation. We discuss several geometries which generate this effect, and introduce a heuristic model which captures the qualitative features. © 2010 The American Physical Society. Source


Cawse J.N.,ProtoLife Inc. | Cawse J.N.,Cawse and Effect LLC | Gazzola G.,ProtoLife Inc. | Gazzola G.,European Center for Living Technology | Packard N.,ProtoLife Inc.
Catalysis Today | Year: 2011

As the pace of experimentation in materials science and catalysis has increased, experimental tactics and strategies have had to adapt to meet the demands of goals of experimentalists, and the spaces they explore. This pace has increased from runs/year to runs/day and sometimes to runs/minute in high-throughput experimentation. Although much of this capacity is used to simply speed up conventional experimental designs, the leading-edge application is discovery of low-probability, high-value occurrences (hits) by searching extensive, complex experimental spaces. Conventional design of experiments (DoE) is not capable of dealing with these issues. Instead, more advanced experimental tactics and strategies must be implemented. After introducing the elements that make an experimental campaign complex, here we present a novel statistical model-based evolutionary experimental strategy and apply it to the optimization of a family of artificial complex systems. With our experiments, we show that such a strategy may significantly reduce the experimental effort required for finding the optima compared to other state-of-the-art evolutionary strategies. © 2010 Elsevier B.V. Source


Serra R.,University of Modena and Reggio Emilia | Serra R.,European Center for Living Technology | Villani M.,University of Modena and Reggio Emilia | Villani M.,European Center for Living Technology | And 3 more authors.
Journal of Theoretical Biology | Year: 2010

The asymptotic dynamics of random Boolean networks subject to random fluctuations is investigated. Under the influence of noise, the system can escape from the attractors of the deterministic model, and a thorough study of these transitions is presented. We show that the dynamics is more properly described by sets of attractors rather than single ones. We generalize here a previous notion of ergodic sets, and we show that the Threshold Ergodic Sets so defined are robust with respect to noise and, at the same time, that they do not suffer from a major drawback of ergodic sets. The system jumps from one attractor to another of the same Threshold Ergodic Set under the influence of noise, never leaving it. By interpreting random Boolean networks as models of genetic regulatory networks, we also propose to associate cell types to Threshold Ergodic Sets rather than to deterministic attractors or to ergodic sets, as it had been previously suggested. We also propose to associate cell differentiation to the process whereby a Threshold Ergodic Set composed by several attractors gives rise to another one composed by a smaller number of attractors. We show that this approach accounts for several interesting experimental facts about cell differentiation, including the possibility to obtain an induced pluripotent stem cell from a fully differentiated one by overexpressing some of its genes. © 2010 Elsevier Ltd. Source

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