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Belles X.,Institute Of Biologia Evolutiva
Annual Review of Entomology | Year: 2010

The increasing availability of insect genomes has revealed a large number of genes with unknown functions and the resulting problem of how to discover these functions. The RNA interference (RNAi) technique, which generates loss-of-function phenotypes by depletion of a chosen transcript, can help to overcome this challenge. RNAi can unveil the functions of new genes, lead to the discovery of new functions for old genes, and find the genes for old functions. Moreover, the possibility of studying the functions of homologous genes in different species can allow comparisons of the genetic networks regulating a given function in different insect groups, thereby facilitating an evolutionary insight into developmental processes. RNAi also has drawbacks and obscure points, however, such as those related to differences in species sensitivity. Disentangling these differences is one of the main challenges in the RNAi field. © 2010 by Annual Reviews All rights reserved. Source


Fort J.,University of Girona | Sole R.V.,University Pompeu Fabra | Sole R.V.,Institute Of Biologia Evolutiva | Sole R.V.,Santa Fe Institute
New Journal of Physics | Year: 2013

Glioblastomas are highly diffuse, malignant tumors that have so far evaded clinical treatment. The strongly invasive behavior of cells in these tumors makes them very resistant to treatment, and for this reason both experimental and theoretical efforts have been directed toward understanding the spatiotemporal pattern of tumor spreading. Although usual models assume a standard diffusion behavior, recent experiments with cell cultures indicate that cells tend to move in directions close to that of glioblastoma invasion, thus indicating that a biased random walk model may be much more appropriate. Here we show analytically that, for realistic parameter values, the speeds predicted by biased dispersal are consistent with experimentally measured data. We also find that models beyond reaction-diffusion-advection equations are necessary to capture this substantial effect of biased dispersal on glioblastoma spread. © IOP Publishing and Deutsche Physikalische Gesellschaft. Source


Sole R.,University Pompeu Fabra | Sole R.,Institute Of Biologia Evolutiva | Sole R.,Santa Fe Institute
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2016

The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general frame- work to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics. © 2016 The Author(s) Published by the Royal Society. All rights reserved. Source


Corominas-Murtra B.,University Pompeu Fabra | Sole R.V.,University Pompeu Fabra | Sole R.V.,Santa Fe Institute | Sole R.V.,Institute Of Biologia Evolutiva
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

Zipf's law is the most common statistical distribution displaying scaling behavior. Cities, populations or firms are just examples of this seemingly universal law. Although many different models have been proposed, no general theoretical explanation has been shown to exist for its universality. Here, we show that Zipf's law is, in fact, an inevitable outcome of a very general class of stochastic systems. Borrowing concepts from Algorithmic Information Theory, our derivation is based on the properties of the symbolic sequence obtained through successive observations over a system with an ubounded number of possible states. Specifically, we assume that the complexity of the description of the system provided by the sequence of observations is the one expected for a system evolving to a stable state between order and disorder. This result is obtained from a small set of mild, physically relevant assumptions. The general nature of our derivation and its model-free basis would explain the ubiquity of such a law in real systems. © 2010 The American Physical Society. Source


Corominas-Murtra B.,University Pompeu Fabra | Corominas-Murtra B.,Institute Of Biologia Evolutiva | Fortuny J.,Autonomous University of Barcelona | Sole R.V.,Santa Fe Institute | Sole R.V.,Institute Of Biologia Evolutiva
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2011

Zipf's law seems to be ubiquitous in human languages and appears to be a universal property of complex communicating systems. Following the early proposal made by Zipf concerning the presence of a tension between the efforts of speaker and hearer in a communication system, we introduce evolution by means of a variational approach to the problem based on Kullback's Minimum Discrimination of Information Principle. Therefore, using a formalism fully embedded in the framework of information theory, we demonstrate that Zipf's law is the only expected outcome of an evolving communicative system under a rigorous definition of the communicative tension described by Zipf. © 2011 American Physical Society. Source

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