545 research outputs found

    Random Networks Tossing Biased Coins

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    In statistical mechanical investigations on complex networks, it is useful to employ random graphs ensembles as null models, to compare with experimental realizations. Motivated by transcription networks, we present here a simple way to generate an ensemble of random directed graphs with, asymptotically, scale-free outdegree and compact indegree. Entries in each row of the adjacency matrix are set to be zero or one according to the toss of a biased coin, with a chosen probability distribution for the biases. This defines a quick and simple algorithm, which yields good results already for graphs of size n ~ 100. Perhaps more importantly, many of the relevant observables are accessible analytically, improving upon previous estimates for similar graphs

    Folding and cytoplasm viscoelasticity contribute jointly to chromosome dynamics

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    The chromosome is a key player of cell physiology, and its dynamics provides valuable information about its physical organization. In both prokaryotes and eukaryotes, the short-time motion of chromosomal loci has been described as a Rouse model in a simple or viscoelastic medium. However, little emphasis has been put on the role played by the folded organization of chromosomes on the local dynamics. Clearly, stress-propagation, and thus dynamics, must be affected by such organization, but a theory allowing to extract such information from data, e.g.\ of two-point correlations, is lacking. Here, we describe a theoretical framework able to answer this general polymer dynamics question, and we provide a general scaling analysis of the stress-propagation time between two loci at a given arclength distance along the chromosomal coordinate. The results suggest a precise way to detect folding information from the dynamical coupling of chromosome segments. Additionally, we realize this framework in a specific theoretical model of a polymer with variable-range interactions in a viscoelastic medium characterized by a tunable scaling exponent, where we derive analytical estimates of the correlation functions.Comment: 14 pages including supplementary material

    Mean-field methods in evolutionary duplication-innovation-loss models for the genome-level repertoire of protein domains

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    We present a combined mean-field and simulation approach to different models describing the dynamics of classes formed by elements that can appear, disappear or copy themselves. These models, related to a paradigm duplication-innovation model known as Chinese Restaurant Process, are devised to reproduce the scaling behavior observed in the genome-wide repertoire of protein domains of all known species. In view of these data, we discuss the qualitative and quantitative differences of the alternative model formulations, focusing in particular on the roles of element loss and of the specificity of empirical domain classes.Comment: 10 Figures, 2 Table

    Physical descriptions of the bacterial nucleoid at large scales, and their biological implications.

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    Recent experimental and theoretical approaches have attempted to quantify the physical organization (compaction and geometry) of the bacterial chromosome with its complement of proteins (the nucleoid). The genomic DNA exists in a complex and dynamic protein-rich state, which is highly organized at various length scales. This has implications for modulating (when not directly enabling) the core biological processes of replication, transcription and segregation. We overview the progress in this area, driven in the last few years by new scientific ideas and new interdisciplinary experimental techniques, ranging from high space- and time-resolution microscopy to high-throughput genomics employing sequencing to map different aspects of the nucleoid-related interactome. The aim of this review is to present the wide spectrum of experimental and theoretical findings coherently, from a physics viewpoint. In particular, we highlight the role that statistical and soft condensed matter physics play in describing this system of fundamental biological importance, specifically reviewing classic and more modern tools from the theory of polymers. We also discuss some attempts toward unifying interpretations of the current results, pointing to possible directions for future investigation

    Feedback topology and XOR-dynamics in Boolean networks with varying input structure

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    We analyse a model of fixed in-degree Random Boolean Networks in which the fraction of input-receiving nodes is controlled by a parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control, and as rich as the one of general Boolean networks. Biologically, it is justified on abstract grounds by the fact that all existing interactions play a dynamical role. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma, this graph ensemble shows a phase transition that separates a tree-like graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact we provide analytical estimates of the maximum period starting from topological considerations

    Hydrodynamic Synchronisation of Model Microswimmers

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    We define a model microswimmer with a variable cycle time, thus allowing the possibility of phase locking driven by hydrodynamic interactions between swimmers. We find that, for extensile or contractile swimmers, phase locking does occur, with the relative phase of the two swimmers being, in general, close to 0 or pi, depending on their relative position and orientation. We show that, as expected on grounds of symmetry, self T-dual swimmers, which are time-reversal covariant, do not phase-lock. We also discuss the phase behaviour of a line of tethered swimmers, or pumps. These show oscillations in their relative phases reminiscent of the metachronal waves of cilia.Comment: 17 pages, 8 figure

    Coherent Hydrodynamic Coupling for Stochastic Swimmers

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    A recently developed theory of stochastic swimming is used to study the notion of coherence in active systems that couple via hydrodynamic interactions. It is shown that correlations between various modes of deformation in stochastic systems play the same role as the relative internal phase in deterministic systems. An example is presented where a simple swimmer can use these correlations to hunt a non-swimmer by forming a hydrodynamic bound state of tunable velocity and equilibrium separation. These results highlight the significance of coherence in the collective behavior of nano-scale stochastic swimmers.Comment: 6 pages, 3 figure

    On the basic computational structure of gene regulatory networks

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    Gene regulatory networks constitute the first layer of the cellular computation for cell adaptation and surveillance. In these webs, a set of causal relations is built up from thousands of interactions between transcription factors and their target genes. The large size of these webs and their entangled nature make difficult to achieve a global view of their internal organisation. Here, this problem has been addressed through a comparative study for {\em Escherichia coli}, {\em Bacillus subtilis} and {\em Saccharomyces cerevisiae} gene regulatory networks. We extract the minimal core of causal relations, uncovering the hierarchical and modular organisation from a novel dynamical/causal perspective. Our results reveal a marked top-down hierarchy containing several small dynamical modules for \textit{E. coli} and \textit{B. subtilis}. Conversely, the yeast network displays a single but large dynamical module in the middle of a bow-tie structure. We found that these dynamical modules capture the relevant wiring among both common and organism-specific biological functions such as transcription initiation, metabolic control, signal transduction, response to stress, sporulation and cell cycle. Functional and topological results suggest that two fundamentally different forms of logic organisation may have evolved in bacteria and yeast.Comment: This article is published at Molecular Biosystems, Please cite as: Carlos Rodriguez-Caso, Bernat Corominas-Murtra and Ricard V. Sole. Mol. BioSyst., 2009, 5 pp 1617--171

    Three Dimensional Annihilation Imaging of Antiprotons in a Penning Trap

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    We demonstrate three-dimensional annihilation imaging of antiprotons trapped in a Penning trap. Exploiting unusual feature of antiparticles, we investigate a previously unexplored regime in particle transport; the proximity of the trap wall. Particle loss on the wall, the final step of radial transport, is observed to be highly non-uniform, both radially and azimuthally. These observations have considerable implications for the production and detection of antihydrogen atoms.Comment: Invited Talk at NNP03, Workshop on Non-Neutral Plasmas, 200
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