173 research outputs found
The Blind Watchmaker Network: Scale-freeness and Evolution
It is suggested that the degree distribution for networks of the
cell-metabolism for simple organisms reflects an ubiquitous randomness. This
implies that natural selection has exerted no or very little pressure on the
network degree distribution during evolution. The corresponding random network,
here termed the blind watchmaker network has a power-law degree distribution
with an exponent gamma >= 2. It is random with respect to a complete set of
network states characterized by a description of which links are attached to a
node as well as a time-ordering of these links. No a priory assumption of any
growth mechanism or evolution process is made. It is found that the degree
distribution of the blind watchmaker network agrees very precisely with that of
the metabolic networks. This implies that the evolutionary pathway of the
cell-metabolism, when projected onto a metabolic network representation, has
remained statistically random with respect to a complete set of network states.
This suggests that even a biological system, which due to natural selection has
developed an enormous specificity like the cellular metabolism, nevertheless
can, at the same time, display well defined characteristics emanating from the
ubiquitous inherent random element of Darwinian evolution. The fact that also
completely random networks may have scale-free node distributions gives a new
perspective on the origin of scale-free networks in general.Comment: 5 pages, 3 figure
Prediction of lethal and synthetically lethal knock-outs in regulatory networks
The complex interactions involved in regulation of a cell's function are
captured by its interaction graph. More often than not, detailed knowledge
about enhancing or suppressive regulatory influences and cooperative effects is
lacking and merely the presence or absence of directed interactions is known.
Here we investigate to which extent such reduced information allows to forecast
the effect of a knock-out or a combination of knock-outs. Specifically we ask
in how far the lethality of eliminating nodes may be predicted by their network
centrality, such as degree and betweenness, without knowing the function of the
system. The function is taken as the ability to reproduce a fixed point under a
discrete Boolean dynamics. We investigate two types of stochastically generated
networks: fully random networks and structures grown with a mechanism of node
duplication and subsequent divergence of interactions. On all networks we find
that the out-degree is a good predictor of the lethality of a single node
knock-out. For knock-outs of node pairs, the fraction of successors shared
between the two knocked-out nodes (out-overlap) is a good predictor of
synthetic lethality. Out-degree and out-overlap are locally defined and
computationally simple centrality measures that provide a predictive power
close to the optimal predictor.Comment: published version, 10 pages, 6 figures, 2 tables; supplement at
http://www.bioinf.uni-leipzig.de/publications/supplements/11-01
On RAF Sets and Autocatalytic Cycles in Random Reaction Networks
The emergence of autocatalytic sets of molecules seems to have played an
important role in the origin of life context. Although the possibility to
reproduce this emergence in laboratory has received considerable attention,
this is still far from being achieved. In order to unravel some key properties
enabling the emergence of structures potentially able to sustain their own
existence and growth, in this work we investigate the probability to observe
them in ensembles of random catalytic reaction networks characterized by
different structural properties. From the point of view of network topology, an
autocatalytic set have been defined either in term of strongly connected
components (SCCs) or as reflexively autocatalytic and food-generated sets
(RAFs). We observe that the average level of catalysis differently affects the
probability to observe a SCC or a RAF, highlighting the existence of a region
where the former can be observed, whereas the latter cannot. This parameter
also affects the composition of the RAF, which can be further characterized
into linear structures, autocatalysis or SCCs. Interestingly, we show that the
different network topology (uniform as opposed to power-law catalysis systems)
does not have a significantly divergent impact on SCCs and RAFs appearance,
whereas the proportion between cleavages and condensations seems instead to
play a role. A major factor that limits the probability of RAF appearance and
that may explain some of the difficulties encountered in laboratory seems to be
the presence of molecules which can accumulate without being substrate or
catalyst of any reaction.Comment: pp 113-12
Dynamics on expanding spaces: modeling the emergence of novelties
Novelties are part of our daily lives. We constantly adopt new technologies,
conceive new ideas, meet new people, experiment with new situations.
Occasionally, we as individuals, in a complicated cognitive and sometimes
fortuitous process, come up with something that is not only new to us, but to
our entire society so that what is a personal novelty can turn into an
innovation at a global level. Innovations occur throughout social, biological
and technological systems and, though we perceive them as a very natural
ingredient of our human experience, little is known about the processes
determining their emergence. Still the statistical occurrence of innovations
shows striking regularities that represent a starting point to get a deeper
insight in the whole phenomenology. This paper represents a small step in that
direction, focusing on reviewing the scientific attempts to effectively model
the emergence of the new and its regularities, with an emphasis on more recent
contributions: from the plain Simon's model tracing back to the 1950s, to the
newest model of Polya's urn with triggering of one novelty by another. What
seems to be key in the successful modelling schemes proposed so far is the idea
of looking at evolution as a path in a complex space, physical, conceptual,
biological, technological, whose structure and topology get continuously
reshaped and expanded by the occurrence of the new. Mathematically it is very
interesting to look at the consequences of the interplay between the "actual"
and the "possible" and this is the aim of this short review.Comment: 25 pages, 10 figure
Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory
Hubbell's 2001 neutral theory unifies biodiversity and biogeography by modelling steady-state distributions of species richness and abundances across spatio-temporal scales. Accurate predictions have issued from its core premise that all species have identical vital rates. Yet no ecologist believes that species are identical in reality. Here I explain this paradox in terms of the ecological equivalence that species must achieve at their coexistence equilibrium, defined by zero net fitness for all regardless of intrinsic differences between them. I show that the distinction of realised from intrinsic vital rates is crucial to evaluating community resilience. An analysis of competitive interactions reveals how zero-sum patterns of abundance emerge for species with contrasting life-history traits as for identical species. I develop a stochastic model to simulate community assembly from a random drift of invasions sustaining the dynamics of recruitment following deaths and extinctions. Species are allocated identical intrinsic vital rates for neutral dynamics, or random intrinsic vital rates and competitive abilities for niche dynamics either on a continuous scale or between dominant-fugitive extremes. Resulting communities have steady-state distributions of the same type for more or less extremely differentiated species as for identical species. All produce negatively skewed log-normal distributions of species abundance, zero-sum relationships of total abundance to area, and Arrhenius relationships of species to area. Intrinsically identical species nevertheless support fewer total individuals, because their densities impact as strongly on each other as on themselves. Truly neutral communities have measurably lower abundance/area and higher species/abundance ratios. Neutral scenarios can be parameterized as null hypotheses for testing competitive release, which is a sure signal of niche dynamics. Ignoring the true strength of interactions between and within species risks a substantial misrepresentation of community resilience to habitat los
Multifractal Spatial Patterns and Diversity in an Ecological Succession
We analyzed the relationship between biodiversity and spatial biomass heterogeneity along an ecological succession developed in the laboratory. Periphyton (attached microalgae) biomass spatial patterns at several successional stages were obtained using digital image analysis and at the same time we estimated the species composition and abundance. We show that the spatial pattern was self-similar and as the community developed in an homogeneous environment the pattern is self-organized. To characterize it we estimated the multifractal spectrum of generalized dimensions Dq. Using Dq we analyze the existence of cycles of heterogeneity during succession and the use of the information dimension D1 as an index of successional stage. We did not find cycles but the values of D1 showed an increasing trend as the succession developed and the biomass was higher. D1 was also negatively correlated with Shannon's diversity. Several studies have found this relationship in different ecosystems but here we prove that the community self-organizes and generates its own spatial heterogeneity influencing diversity. If this is confirmed with more experimental and theoretical evidence D1 could be used as an index, easily calculated from remote sensing data, to detect high or low diversity areas
Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death
We analyze the dynamic properties of 10^7 words recorded in English, Spanish
and Hebrew over the period 1800--2008 in order to gain insight into the
coevolution of language and culture. We report language independent patterns
useful as benchmarks for theoretical models of language evolution. A
significantly decreasing (increasing) trend in the birth (death) rate of words
indicates a recent shift in the selection laws governing word use. For new
words, we observe a peak in the growth-rate fluctuations around 40 years after
introduction, consistent with the typical entry time into standard dictionaries
and the human generational timescale. Pronounced changes in the dynamics of
language during periods of war shows that word correlations, occurring across
time and between words, are largely influenced by coevolutionary social,
technological, and political factors. We quantify cultural memory by analyzing
the long-term correlations in the use of individual words using detrended
fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined,
eliminates substantial material and incorporates referee comments: 19 pages,
14 figures, 3 table
Persistence Increases with Diversity and Connectance in Trophic Metacommunities
We are interested in understanding if metacommunity dynamics contribute to the persistence of complex spatial food webs subject to colonization-extinction dynamics. We study persistence as a measure of stability of communities within discrete patches, and ask how do species diversity, connectance, and topology influence it in spatially structured food webs.We answer this question first by identifying two general mechanisms linking topology of simple food web modules and persistence at the regional scale. We then assess the robustness of these mechanisms to more complex food webs with simulations based on randomly created and empirical webs found in the literature. We find that linkage proximity to primary producers and food web diversity generate a positive relationship between complexity and persistence in spatial food webs. The comparison between empirical and randomly created food webs reveal that the most important element for food web persistence under spatial colonization-extinction dynamics is the degree distribution: the number of prey species per consumer is more important than their identity.With a simple set of rules governing patch colonization and extinction, we have predicted that diversity and connectance promote persistence at the regional scale. The strength of our approach is that it reconciles the effect of complexity on stability at the local and the regional scale. Even if complex food webs are locally prone to extinction, we have shown their complexity could also promote their persistence through regional dynamics. The framework we presented here offers a novel and simple approach to understand the complexity of spatial food webs
Quasispecies Spatial Models for RNA Viruses with Different Replication Modes and Infection Strategies
Empirical observations and theoretical studies suggest that viruses may use different replication strategies to amplify their genomes, which impact the dynamics of mutation accumulation in viral populations and therefore, their fitness and virulence. Similarly, during natural infections, viruses replicate and infect cells that are rarely in suspension but spatially organized. Surprisingly, most quasispecies models of virus replication have ignored these two phenomena. In order to study these two viral characteristics, we have developed stochastic cellular automata models that simulate two different modes of replication (geometric vs stamping machine) for quasispecies replicating and spreading on a two-dimensional space. Furthermore, we explored these two replication models considering epistatic fitness landscapes (antagonistic vs synergistic) and different scenarios for cell-to-cell spread, one with free superinfection and another with superinfection inhibition. We found that the master sequences for populations replicating geometrically and with antagonistic fitness effects vanished at low critical mutation rates. By contrast, the highest critical mutation rate was observed for populations replicating geometrically but with a synergistic fitness landscape. Our simulations also showed that for stamping machine replication and antagonistic epistasis, a combination that appears to be common among plant viruses, populations further increased their robustness by inhibiting superinfection. We have also shown that the mode of replication strongly influenced the linkage between viral loci, which rapidly reached linkage equilibrium at increasing mutations for geometric replication. We also found that the strategy that minimized the time required to spread over the whole space was the stamping machine with antagonistic epistasis among mutations. Finally, our simulations revealed that the multiplicity of infection fluctuated but generically increased along time
Modelling avalanches in martensites
Solids subject to continuous changes of temperature or mechanical load often
exhibit discontinuous avalanche-like responses. For instance, avalanche
dynamics have been observed during plastic deformation, fracture, domain
switching in ferroic materials or martensitic transformations. The statistical
analysis of avalanches reveals a very complex scenario with a distinctive lack
of characteristic scales. Much effort has been devoted in the last decades to
understand the origin and ubiquity of scale-free behaviour in solids and many
other systems. This chapter reviews some efforts to understand the
characteristics of avalanches in martensites through mathematical modelling.Comment: Chapter in the book "Avalanches in Functional Materials and
Geophysics", edited by E. K. H. Salje, A. Saxena, and A. Planes. The final
publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-45612-6_
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