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At least 19 recordsLinked to original sources

arXiv2011

Universal spectrum for DNA base CG frequency distribution in Takifugu rubripes (Puffer fish) genome

The frequency distribution of DNA bases A, C, G, T exhibit fractal fluctuations ubiquitous to dynamical systems in nature. The power spectra of fractal fluctuations exhibit inverse power law form signifying long-range correlations between local (small-scale) and global (large-scale) perturbations. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts that the probability distribution of eddy amplitudes and the variance (square of eddy amplitude)spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. The model predicted distribution is very close to statistical normal distribution for fluctuations within two standard deviations from the mean and exhibits a fat long tail. In this paper it is shown that DNA base CG frequency distribution in Takifugu rubripes (Puffer fish) Genome Release 4 exhibit universal inverse power law form consistent with model prediction. The observed long-range correlations in the DNA bases implies that the non-coding 'junk' or 'selfish' DNA which appear to be redundant, may also contribute to the efficient functioning of the protein coding DNA, a result supported by recent studies.

physics.gen-ph↗

arXiv2007

Tuning Spontaneous Emission versus Forster Energy Transfer in Biological Systems by Manipulating the Density of Photonic States

We theoretically discuss how to tune the competition between Forster transfer and spontaneous emission in a continuous and nondestructive fashion. The proposed approach is especially suitable for delicate biological systems like light harvesting complexes and fluorescent protein oligomers. We demonstrate that the manipulation of the density of photonic states at the emission frequency of the energy donor results in a change of the quantum efficiencies of the competing energy transfer and spontaneous emission processes. This change will be manifested in a modification of the donor and acceptor emission intensities. Thus, by controlling the local density of photonic states Forster coupled systems can be manipulated and analyzed without the need to physically separate donor and acceptor chromophores for individual analysis, which is of interest, for example, for oligomeric reef coral fluorescent proteins.

physics.chem-ph↗

arXiv2007

Two computational regimes of a single-compartment neuron separated by a planar boundary in conductance space

Recent in vitro data show that neurons respond to input variance with varying sensitivities. Here, we demonstrate that Hodgkin-Huxley (HH) neurons can operate in two computational regimes, one that is more sensitive to input variance (differentiating) and one that is less sensitive (integrating). A boundary plane in the 3D conductance space separates these two regimes. For a reduced HH model, this plane can be derived analytically from the V nullcline, thus suggesting a means of relating biophysical parameters to neural computation by analyzing the neuron's dynamical system.

q-bio.NC↗

arXiv2007

High Resolution Mapping of Phase Behavior in a Ternary Lipid Mixture: Do Lipid-Raft Phase Boundaries Depend on Sample-Prep Procedure?

For some time now, we have been using a FRET-based strategy to make high-resolution studies of phase behavior in ternary lipid-raft membrane mixtures. Our FRET experiments can be carried out on ordinary, polydisperse multilamellar vesicle suspensions, so we are able to prepare our samples according to a procedure that was designed specifically to guard against artifactual phase separation. In some respects (i.e., the number and nature of two-phase regions observed), our phase diagrams are consistent with previously published reports. However, in other respects (i.e., overall size of miscibility gaps, phase boundary locations and their dependence on temperature) there are clear differences. Here we present FRET data taken in DOPC/DPPC/Cholesterol mixtures at 25.0, 35.0 and 45.0oC. Comparisons between our results and previously reported phase boundaries suggest that lipid-raft mixtures may be particularly susceptible to demixing effects during sample preparation.

physics.bio-ph↗

arXiv2007

RNA polymerase motors on DNA track: effects of traffic congestion on RNA synthesis

RNA polymerase (RNAP) is an enzyme that synthesizes a messenger RNA (mRNA) strand which is complementary to a single-stranded DNA template. From the perspective of physicists, an RNAP is a molecular motor that utilizes chemical energy input to move along the track formed by a ssDNA. In some circumstances, which are described in this paper, a large number of RNAPs move simultaneously along the same track. We refer to such collective movements of the RNAPs as RNAP traffic because of the similarities between the collective dynamics of the RNAPs on ssDNA track and that of vehicles in highway traffic. In this paper we develop a theoretical model for RNAP traffic by incorporating the steric interactions between RNAPs as well as the mechano-chemical cycle of individual RNAPs during the elongation of the mRNA. By a combination of analytical and numerical techniques, we calculate the rates of mRNA synthesis and the average density profile of the RNAPs on the ssDNA track. We also suggest novel experiments for testing our theoretical predictions.

physics.bio-ph↗

arXiv2007

p-Adic Degeneracy of the Genetic Code

Degeneracy of the genetic code is a biological way to minimize effects of the undesirable mutation changes. Degeneration has a natural description on the 5-adic space of 64 codons $\mathcal{C}_5 (64) = \{n_0 + n_1 5 + n_2 5^2 : n_i = 1, 2, 3, 4 \} ,$ where $n_i$ are digits related to nucleotides as follows: C = 1, A = 2, T = U = 3, G = 4. The smallest 5-adic distance between codons joins them into 16 quadruplets, which under 2-adic distance decay into 32 doublets. p-Adically close codons are assigned to one of 20 amino acids, which are building blocks of proteins, or code termination of protein synthesis. We shown that genetic code multiplets are made of the p-adic nearest codons.

q-bio.GN↗

arXiv2007

Continuous or discrete attractors in neural circuits? A self-organized switch at maximal entropy

A recent experiment suggests that neural circuits may alternatively implement continuous or discrete attractors, depending on the training set up. In recurrent neural network models, continuous and discrete attractors are separately modeled by distinct forms of synaptic prescriptions (learning rules). Here, we report a solvable network model, endowed with Hebbian synaptic plasticity, which is able to learn either discrete or continuous attractors, depending on the frequency of presentation of stimuli and on the structure of sensory coding. A continuous attractor is learned when experience matches sensory coding, i.e. when the distribution of experienced stimuli matches the distribution of preferred stimuli of neurons. In that case, there is no processing of sensory information and neural activity displays maximal entropy. If experience goes beyond sensory coding, processing is initiated and the continuous attractor is destabilized into a set of discrete attractors.

physics.bio-ph↗

arXiv2008

Control parameters in turbulence, Self Organized Criticality and ecosystems

From the starting point of the well known Reynolds number of fluid turbulence we propose a control parameter $R$ for a wider class of systems including avalanche models that show Self Organized Criticality (SOC) and ecosystems. $R$ is related to the driving and dissipation rates and from similarity analysis we obtain a relationship $R\sim N^{β_N}$ where $N$ is the number of degrees of freedom. The value of the exponent $β_N$ is determined by detailed phenomenology but its sign follows from our similarity analysis. For SOC, $R=h/ε$ and we show that $β_N<0$ hence we show independent of the details that the transition to SOC is when $R \to 0$, in contrast to fluid turbulence, formalizing the relationship between turbulence (since $β_N >0$, $R \to \infty$) and SOC ($R=h/ε\to 0$). A corollary is that SOC phenomenology, that is, power law scaling of avalanches, can persist for finite $R$ with unchanged exponent if the system supports a sufficiently large range of lengthscales; necessary for SOC to be a candidate for physical systems. We propose a conceptual model ecosystem where $R$ is an observable parameter which depends on the rate of throughput of biomass or energy; we show this has $β_N>0$, so that increasing $R$ increases the abundance of species, pointing to a critical value for species 'explosion'.

physics.bio-ph↗

arXiv2007

Structure-Activity Relationship Investigation of Some New Tetracyclines by Electronic Index Methodology

Tetracyclines are an old class of molecules that constitute a broad-spectrum antibiotics. Since the first member of tetracycline family were isolated, the clinical importance of these compounds as therapeutic and prophylactic agents against a wide range of infections has stimulated efforts to define their mode of action as inhibitors of bacterial reproduction. We used three SAR methodologies for the analysis of biological activity of a set of 104 tetracycline compounds. Our calculation were carried out using the semi-empirical Austin Method One (AM1) and Parametric Method 3 (PM3). Electronic Indices Methodology (EIM), Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) were applied to the classification of 14 old and 90 new proposed derivatives of tetracyclines. Our results make evident the importance of EIM descriptors in pattern recognition and also show that the EIM can be effectively used to predict the biological activity of Tetracyclines.

q-bio.BM↗

arXiv2010

Are biological neurons that vicious ? Or only their models ?

This paper has been withdrawn. Its main conclusions have been published in "On dynamics of integrate-and-fi re neural networks with conductance based synapses", arXiv:0709.4370 and http://www.frontiersin.org/computational_neuroscience/10.3389/neuro.10/002.2008/abstract

physics.bio-ph↗

arXiv2007

Can magnetism-assisted quasiperiodic structures in Russell-FeS `bubbles' offer a quantum coherent origin of life?

This paper seeks to expand the scope of the alkaline seepage site hydrothermal mound scenario of Russell et al, by appealing to its wider canvas for hypothesizing self-assembly of gregite clusters via interplay of forces within the gel phase of FeS membranes: directed heat transport a la Rayleigh-Benard convection for dissociation, vs oriented attachment (small clusters) and magnetic forces (large clusters) for association, the latter assisted by magnetic mound constituents. The directed movement of tiny clusters through cluster layers are reminiscent of processes like budding, molecular motors, pre-RNA world on the lines of Cairns-Smith's hypothesis, and optical polarity. Higher rate of (soft) multinucleate formation vs growth rate of (rigid) microcrystals, correlates with icosahedral (forbidden crystallographically!) framboidal morphology. This pattern indicates a link to phylotaxis, thus reinforcing the quasi-periodicity connection which can provide a natural access to features like surface limit, anomalous transport and low thermal conductivity, while facilitating diffusion through clusters. And magnetism offers a hierarchy of features: primordial multicellularity; phase correlations of assembled molecules; overcoming thermal decoherence. These dynamical nested structures offer possibilities for iterative computations, adaptive learning, and coherent quantum searches. The link between enzymatic FeS clusters and the Hadean ocean floor is seen as part of a larger conceptual framework uncovering a role for Magnetism and the Origin of Life.

cond-mat.soft↗

arXiv2007

Coupling Lattice Boltzmann with Atomistic Dynamics for the multiscale simulation of nano-biological flows

We describe a recent multiscale approach based on the concurrent coupling of constrained molecular dynamics for long biomolecules with a mesoscopic lattice Boltzmann treatment of solvent hydrodynamics. The multiscale approach is based on a simple scheme of exchange of space-time information between the atomistic and mesoscopic scales and is capable of describing self-consistent hydrodynamic effects on molecular motion at a computational cost which scales linearly with both solute size and solvent volume. For an application of our multiscale method, we consider the much studied problem of biopolymer translocation through nanopores: we find that the method reproduces with remarkable accuracy the statistical scaling behavior of the translocation process and provides valuable insight into the cooperative aspects of biopolymer and hydrodynamic motion.

physics.bio-ph↗

arXiv2009

Endogenous versus Exogenous Origins of Diseases

Many illnesses are associated with an alteration of the immune system homeostasis due to any combination of factors, including exogenous bacterial insult, endogenous breakdown (e.g., development of a disease that results in immuno suppression), or an exogenous hit like surgery that simultaneously alters immune responsiveness and provides access to bacteria, or genetic disorder. We conjecture that, as a consequence of the co-evolution of the immune system of individuals with the ecology of pathogens, the homeostasis of the immune system requires the influx of pathogens. This allows the immune system to keep the ever present pathogens under control and to react and adjust fast to bursts of infections. We construct the simplest and most general system of rate equations which describes the dynamics of five compartments: healthy cells, altered cells, adaptive and innate immune cells, and pathogens. We study four regimes obtained with or without auto-immune disorder and with or without spontaneous proliferation of infected cells. Over all regimes, we find that seven different states are naturally described by the model: (i) strong healthy immune system, (ii) healthy organism with evanescent immune cells, (iii) chronic infections, (iv) strong infections, (v) cancer, (vi) critically ill state and (vii) death. The analysis of stability conditions demonstrates that these seven states depend on the balance between the robustness of the immune system and the influx of pathogens.

physics.bio-ph↗

arXiv2007

Stochastic extinction of epidemics in large populations and role of vaccinations

We investigate stochastic extinction in an epidemic model and the impact of random vaccinations in large populations formulated in terms of an optimal escape path. We find that different random vaccination strategies can have widely different results in decreasing expected time till extinction, for the same total amount of vaccines used. Vaccination strategies are considered in terms of two parameters: average frequency of vaccinations, given by $γ$, and the amplitude of the vaccinations, $ε$, where $ε\ll 1$ refers to the proportion of the population being vaccinated at some particular instant. It is found that while the average number of individuals vaccinated per unit time, $γε$, is kept constant, the particular values of $γ$ and $ε$ can play a highly significant role in increasing the chance of epidemic extinction. The findings suggest that expected time till extinction can be significantly shortened if less frequent vaccinations occur in larger groups, corresponding to low $γ$, high $ε$ strategy.

physics.bio-ph↗

arXiv2007

Steady-State Chemotactic Response in E. coli

The bacterium E. coli maneuvers itself to regions with high chemoattractant concentrations by performing two stereotypical moves: `runs', in which it moves in near straight lines, and `tumbles', in which it does not advance but changes direction randomly. The duration of each move is stochastic and depends upon the chemoattractant concentration experienced in the recent past. We relate this stochastic behavior to the steady-state density of a bacterium population, and we derive the latter as a function of chemoattractant concentration. In contrast to earlier treatments, here we account for the effects of temporal correlations and variable tumbling durations. A range of behaviors obtains, that depends subtly upon several aspects of the system - memory, correlation, and tumbling stochasticity in particular.

q-bio.CB↗

arXiv2008

Absolute FKBP binding affinities obtained via non-equilibrium unbinding simulations

We compute absolute binding affinities for two ligands bound to the FKBP protein using non-equilibrium unbinding simulations. The methodology is straight-forward, requiring little or no modification to many modern molecular simulation packages. The approach makes use of a physical pathway, eliminating the need for complicated alchemical decoupling schemes. Results of this study are promising. For the ligands studied here the binding affinities are typically estimated within less than 4.0 kJ/mol of the target values; and the target values are within less than 1.0 kJ/mol of experiment. These results suggest that non-equilibrium simulation could provide a simple and robust means to estimate protein-ligand binding affinities.

physics.bio-ph↗

arXiv2007

Finite size effects and symmetry breaking in the evolution of networks of competing Boolean nodes

The effects of the finite size of the network on the evolutionary dynamics of a Boolean network are analyzed. In the model considered, Boolean networks evolve via a competition between nodes that punishes those in the majority. It is found that finite size networks evolve in a fundamentally different way than infinitely large networks do. The symmetry of the evolutionary dynamics of infinitely large networks that selects for canalizing Boolean functions is broken in the evolutionary dynamics of finite size networks. In finite size networks there is an additional selection for input inverting Boolean functions that output a value opposite to the majority of input values. These results are revealed through an empirical study of the model that calculates the frequency of occurrence of the different possible Boolean functions. Classes of functions are found to occur with the same frequency. Those classes depend on the symmetry of the evolutionary dynamics and correspond to orbits of the relevant symmetry group. The empirical results match analytic results, determined by utilizing Polya's theorem, for the number of orbits expected in both finite size and infinitely large networks. The reason for the symmetry breaking in the evolutionary dynamics is found to be due to the need for nodes in finite size networks to behave differently in order to cooperate so that the system collectively performs as well as possible. The results suggest that both finite size effects and symmetry are important for understanding the evolution of real-world complex networks, including genetic regulatory networks.

cond-mat.stat-mech↗

arXiv2007

Parallel multiscale modeling of biopolymer dynamics with hydrodynamic correlations

We employ a multiscale approach to model the translocation of biopolymers through nanometer size pores. Our computational scheme combines microscopic Molecular Dynamics (MD) with a mesoscopic Lattice Boltzmann (LB) method for the solvent dynamics, explicitly taking into account the interactions of the molecule with the surrounding fluid. We describe an efficient parallel implementation of the method which exhibits excellent scalability on the Blue Gene platform. We investigate both dynamical and statistical aspects of the translocation process by simulating polymers of various initial configurations and lengths. For a representative molecule size, we explore the effects of important parameters that enter in the simulation, paying particular attention to the strength of the molecule-solvent coupling and of the external electric field which drives the translocation process. Finally, we explore the connection between the generic polymers modeled in the simulation and DNA, for which interesting recent experimental results are available.

physics.comp-ph↗