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At least 55 records · Page 3Linked to original sources

Managing catastrophic changes in a collective

We address the important practical issue of understanding, predicting and eventually controlling catastrophic endogenous changes in a collective. Such large internal changes arise as macroscopic manifestations of the microscopic dynamics, and their presence can be regarded as one of the defining features of an evolving complex system. We consider the specific case of a multi-agent system related to the El Farol bar model, and show explicitly how the information concerning such large macroscopic changes becomes encoded in the microscopic dynamics. Our findings suggest that these large endogenous changes can be avoided either by pre-design of the collective machinery itself, or in the post-design stage via continual monitoring and occasional `vaccinations'.

cond-mat.dis-nn↗

Critical dynamics of DNA denaturation

We present detailed molecular dynamics results for the displacement autocorrelation spectra of the Peyrard-Bishop model of thermal DNA denaturation. As the phase transition is approached, the spectra depend on whether the wavelength is smaller than, or exceeds the correlation length. In the first case, the spectra are dominated by a single peak, whose frequency approaches the bare acoustic frequency of the harmonic chain, and whose linewidth approaches zero as $T_c-T$. In the second case, a central peak (CP) feature is dominant, accounting for most of the weight; the linewidth of the CP appears to be temperature-independent. We also present force autocorrelation spectra which may be relevant for analyzing the statistical properties of localized modes.

cond-mat.stat-mech↗

Coarse-grained simulation of polymer translocation through an artificial nanopore

The translocation of a macromolecule through a nanometer-sized pore is an interesting process with important applications in the development of biosensors for single--molecule analysis and in drug delivery and gene therapy. We have carried out a molecular dynamics simulation study of electrophoretic translocation of a charged polymer through an artificial nanopore to explore the feasibility of semiconductor--based nanopore devices for ultra--fast DNA sequencing. The polymer is represented by a simple bead--spring model designed to yield an appropriate coarse-grained description of the phosphate backbone of DNA in salt--free aqueous solution. A detailed analysis of single translocation event is presented to assess whether the passage of individual ions through the pore can be detected by a nanoscale field--effect transistor by measuring variations in electrostatic potential during polymer translocation. We find that it is possible to identify single events corresponding to the passage of counterions through the pore, but that discrimination of individual ions on the polymer chain based on variations in electrostatic potential is problematic. Several distinct stages in the translocation process are identified, characterized by changes in polymer conformation and by variations in the magnitude and direction of the internal electric field induced by the fluctuating charge distribution. The dependence of the condensed fraction of counterions on Bjerrum length leads to significant changes in polymer conformation, which profoundly affect the dynamics of electrophoresis and translocation.

cond-mat.stat-mech↗

Sum rules for free energy and frequency distribution of DNA dinucleotides

The large discrepancy between the values of the free energy for DNA dinucleotides (or dimers) measured by different teams has raised a yet unsettled debate. Here the free energy is fitted by a three parameter empiric formula derived in the framework of the crystal basis model of genetic code. Sum rules are derived and compared satisfactorily with the data. On the basis of theoretical and phenomenological arguments, a relation between the correlation functions of dimer distribution and the free energy is assumed. From consistency conditions, sum rules are derived. A check of these conditions with different samples of experimental data is performed, allowing us to argue on the reliability of the different sets of experimental data.

cond-mat↗

A Growth Model for Dna Evolution (submitted to Nature)

We introduce a simple model for DNA evolution. Using the method of Peng et al.$^1$, we investigate the fractal properties of the system. For small chains and chains of intermediate size we find a fractal exponent that indicates the existence of long-range correlations, as in real DNA sequences. However, when very large chains are studied the fractal exponent asymptotically converge to the value of a random sequence. We verify that the mutations are responsible for the apparent existence of long-range correlations.

cond-mat↗

Self-Organized Criticality in the Model of Biological Evolution Describing Interaction of "Coenophilous" and " Coenophobous" Species

The modification of the model of P.Bak and K.Sneppen of the self-organized biological evolution is proposed on the basis of a formalization of the scheme of the biosphere evolution suggested by O.V.Kovalev. This scheme is regarded as one approximating the realistic model of the ecosystem evolution. The fundamental difference between "coenophilous" species and "coenophobous" ones in respect to their reaction on the external environment is represented. The dynamics of the modified model as well as that of the model of P.Bak and K. Sneppen possesses the most important features of selforganized criticality: the avalanche-like processes and the punctuated equilibrium. The results obtained by using the numerical experiment for the study of these phenomena are presented.

cond-mat↗

Dynamics of Random Networks: Connectivity and First Order Phase Transitions

The connectivity of individual neurons of large neural networks determine both the steady state activity of the network and its answer to external stimulus. Highly diluted random networks have zero activity. We show that increasing the network connectivity the activity changes discontinuously from zero to a finite value as a critical value in the connectivity is reached. Theoretical arguments and extensive numerical simulations indicate that the origin of this discontinuity in the activity of random networks is a first order phase transition from an inactive to an active state as the connectivity of the network is increased.

cond-mat↗

Kinetics of Phase Ordering in a Two-Component Fluid Membrane

We present a novel Monte Carlo simulation of the phase separation dynamics of a model fluid membrane. Such a phase segregation induces shape changes of the membrane and results in local `budding' under favourable conditions. We present a preliminary investigation of the nucleation regime and compute a variety of growth laws. Our study indicates that membranes with high viscosity, buckle on account of phase segregation. We discuss the relation between this dynamical buckling and the phenomenon of `capping' seen in biological membranes.

cond-mat↗

Simple Model of Large Scale Organization in Evolution

A mathematical model of interacting species filling ecological niches left by the extinction of others is introduced. Species organize themselves into genera of all sizes. The size of a genus on average grows linearly with its age, confirming a general relation between Age and Area proposed by Willis. The ecology exhibits punctuated equilibrium. Analytic and numerical results show that the probability distribution of genera sizes, genera lifetimes, and extinction event sizes are the same power law $P(x) \sim 1/x^2$, consistent with paleontological data.

cond-mat↗

Energetics of thermal ratchet models

Several stochastic models called thermal ratchet models have been recently proposed to analyze the motor proteins such as myosin and kinesin,etc. We propose a method to study the energetics of those models, and show how the rate of energy consumption and the energy dissipation are evaluated. As a demonstration we consider "Feynman's ratchet", a typical fluctuating heat engine.

cond-mat.stat-mech↗

Protein Folding Kinetics: Time Scales, Pathways, and Energy Landscapes in Terms of Sequence Dependent Properties

The folding kinetics of a number of sequences for off-lattice continuum model of proteins is studied using Langevin simulations at two values of the friction coefficient. We show that there is a remarkable correlation between folding times, $τ_{F}$, and $σ= (T_{θ} - T_{F})/T_{θ} $, where $T_{θ}$ and $T_{F}$ are the equilibrium collapse and folding transition temperatures, respectively. The microscopic dynamics reveals several scenarios for the refolding kinetics depending on the values of $σ$. Proteins with small $σ$ reach the native conformation via a nucleation collapse mechanism and their energy landscape is characterized by single dominant native basin of attraction. Proteins with large $σ$ get trapped in competing basins of attraction, in which they adopt misfolded structures. In this case only a small fraction of molecules $Φ$ access the native state rapidly, the majority of them approach the native state by a three stage multipathway mechanism. The partition factor $Φ$ is determined by $σ$: smaller the value of $σ$ larger is $Φ$. The qualitative aspects of our results are found to be independent of the friction coefficient. Estimates for time scales for folding of small proteins via a nucleation collapse mechanism are presented.

cond-mat.stat-mech↗

Sensitivity to Initial Conditions and Nonextensivity in Biological Evolution

We consider biological evolution as described within the Bak and Sneppen 1993 model. We exhibit, at the self-organized critical state, a power-law sensitivity to the initial conditions, calculate the associated exponent, and relate it to the recently introduced nonextensive thermostatistics. The scenario which here emerges without tuning strongly reminds that of the tuned onset of chaos in say logistic-like onedimensional maps. We also calculate the dynamical exponent z.

cond-mat.stat-mech↗

Competition in a Fitness Landscape

We present an extension of Eigen's model for quasi-species including the competition among individuals, proposed as the simplest mechanism for the formation of new species in a smooth fitness landscape. We are able to obtain analytically the critical threshold for species formation. The comparison with numerical simulations is very good.

cond-mat.stat-mech↗

Suggested Model for the Origin of Mosaic Structure of DNA

In view of the critical behavior exhibited by a statistical model describing a one dimensional crystal containing isotopic impurities and the fact that for impurity mass parameter 3 times the host mass the critical temperature can attain very high values, we suggest that the mosaic structure displayed by certain nucleic acids (DNA) of eukaryotic organisms might have had its origins in a phenomenon of condensation of codons ocurred at prebiotic conditions. An appropriated map of that model onto some of the DNA features allows one to predict power law behavior for both correlation functions and exons size distribution in binary sequences of nucleotides which are distinguished by their protein coding or noncoding functions. Preliminary studies of these quantities performed on intron-containing sequences from GenBank are presented here.

cond-mat↗

Kinetic Partitioning Mechanism as a Unifying Theme in the Folding of Biomolecules

We present a unified framework for folding kinetics of proteins and RNA. The basis for this framework relies on the notion of topological frustration, which gives rise to several competing basins of attraction (CBA) in addition to the native basin of attraction (NBA) on the free energy surface. A rough free energy surface results in direct and indirect pathways to the NBA, i.e., a kinetic partitioning mechanism (KPM). The unified framework for folding kinetics allows us to propose a foldability principle, according to which fast folding sequences are characterized by the folding transition temperature $T_{F}$ being close to the collapse transition temperature $T_{θ}$. Biomolecules, for which foldability principle is satisfied, such as small proteins and tRNAs, are expected to fold rapidly with two-state kinetics. Estimates for the multiple time scales in KPM are also given.

cond-mat.soft↗

Neural Networks

We review the theory of neural networks, as it has emerged in the last ten years or so within the physics community, emphasizing questions of biological relevance over those of importance in mathematical statistics and machine learning theory.

cond-mat.dis-nn↗

Protein folding and heteropolymers

We present a statistical mechanics approach to the protein folding problem. We first review some of the basic properties of proteins, and introduce some physical models to describe their thermodynamics. These models rely on a random heteropolymeric description of these non random biomolecules. Various kinds of randomness are investigated, and the connection with disordered systems is discussed. We conclude by a brief study of the dynamics of proteins.

cond-mat.dis-nn↗

How fast can fluids squeeze through micro-pores?

We use a one dimensional symmetric exclusion model to study pressure and osmosis driven flows through molecular-sized channels, such as biological membrane channels and zeolite pores. Analytic expressions are found for the steady-state flow which show rich nonlinear behavior. We find a maximum in the flow rates depending upon pore radius, pore energetics, reservoir temperature, and driving force. We also present exact mean-field results of transport through pores with internal defects. The interesting nonlinear dependences suggest numerous diagnostic experiments in biological and zeolitic systems which may reveal the features presented.

cond-mat.soft↗