91 research outputs found

    Numerical evidence for relevance of disorder in a Poland-Scheraga DNA denaturation model with self-avoidance: Scaling behavior of average quantities

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    We study numerically the effect of sequence heterogeneity on the thermodynamic properties of a Poland-Scheraga model for DNA denaturation taking into account self-avoidance, i.e. with exponent c_p=2.15 for the loop length probability distribution. In complement to previous on-lattice Monte Carlo like studies, we consider here off-lattice numerical calculations for large sequence lengths, relying on efficient algorithmic methods. We investigate finite size effects with the definition of an appropriate intrinsic length scale x, depending on the parameters of the model. Based on the occurrence of large enough rare regions, for a given sequence length N, this study provides a qualitative picture for the finite size behavior, suggesting that the effect of disorder could be sensed only with sequence lengths diverging exponentially with x. We further look in detail at average quantities for the particular case x=1.3, ensuring through this parameter choice the correspondence between the off-lattice and the on-lattice studies. Taken together, the various results can be cast in a coherent picture with a crossover between a nearly pure system like behavior for small sizes N < 1000, as observed in the on-lattice simulations, and the apparent asymptotic behavior indicative of disorder relevance, with an (average) correlation length exponent \nu_r >= 2/d (=2).Comment: Latex, 33 pages with 15 postscript figure

    Numerical study of the disordered Poland-Scheraga model of DNA denaturation

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    We numerically study the binary disordered Poland-Scheraga model of DNA denaturation, in the regime where the pure model displays a first order transition (loop exponent c=2.15>2c=2.15>2). We use a Fixman-Freire scheme for the entropy of loops and consider chain length up to N=4105N=4 \cdot 10^5, with averages over 10410^4 samples. We present in parallel the results of various observables for two boundary conditions, namely bound-bound (bb) and bound-unbound (bu), because they present very different finite-size behaviors, both in the pure case and in the disordered case. Our main conclusion is that the transition remains first order in the disordered case: in the (bu) case, the disorder averaged energy and contact densities present crossings for different values of NN without rescaling. In addition, we obtain that these disorder averaged observables do not satisfy finite size scaling, as a consequence of strong sample to sample fluctuations of the pseudo-critical temperature. For a given sample, we propose a procedure to identify its pseudo-critical temperature, and show that this sample then obeys first order transition finite size scaling behavior. Finally, we obtain that the disorder averaged critical loop distribution is still governed by P(l)1/lcP(l) \sim 1/l^c in the regime lNl \ll N, as in the pure case.Comment: 12 pages, 13 figures. Revised versio

    A stitch in time: Efficient computation of genomic DNA melting bubbles

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    Background: It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses the challenge that a generic search through all combinations of bubble starts and ends is quadratic. Results: An efficient algorithm is described, which shows that the time complexity of the task is O(NlogN) rather than quadratic. The algorithm exploits that bubble lengths may be limited, but without a prior assumption of a maximal bubble length. No approximations, such as windowing, have been introduced to reduce the time complexity. More than just finding the bubbles, the algorithm produces a stitch profile, which is a probabilistic graphical model of bubbles and helical regions. The algorithm applies a probability peak finding method based on a hierarchical analysis of the energy barriers in the Poland-Scheraga model. Conclusions: Exact and fast computation of genomic stitch profiles is thus feasible. Sequences of several megabases have been computed, only limited by computer memory. Possible applications are the genome-wide comparisons of bubbles with promotors, TSS, viral integration sites, and other melting-related regions.Comment: 16 pages, 10 figure

    Probabilistic sequence alignments: realistic models with efficient algorithms

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    Alignment algorithms usually rely on simplified models of gaps for computational efficiency. Based on an isomorphism between alignments and physical helix-coil models, we show in statistical mechanics that alignments with realistic laws for gaps can be computed with fast algorithms. Improved performances of probabilistic alignments with realistic models of gaps are illustrated. Probabilistic and optimization formulations are compared, with potential implications in many fields and perspectives for computationally efficient extensions to Markov models with realistic long-range interactions

    Delocalization transition of the selective interface model: distribution of pseudo-critical temperatures

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    According to recent progress in the finite size scaling theory of critical disordered systems, the nature of the phase transition is reflected in the distribution of pseudo-critical temperatures Tc(i,L)T_c(i,L) over the ensemble of samples (i)(i) of size LL. In this paper, we apply this analysis to the delocalization transition of an heteropolymeric chain at a selective fluid-fluid interface. The width ΔTc(L)\Delta T_c(L) and the shift [Tc()Tcav(L)][T_c(\infty)-T_c^{av}(L)] are found to decay with the same exponent L1/νRL^{-1/\nu_{R}}, where 1/νR0.261/\nu_{R} \sim 0.26. The distribution of pseudo-critical temperatures Tc(i,L)T_c(i,L) is clearly asymmetric, and is well fitted by a generalized Gumbel distribution of parameter m3m \sim 3. We also consider the free energy distribution, which can also be fitted by a generalized Gumbel distribution with a temperature dependent parameter, of order m0.7m \sim 0.7 in the critical region. Finally, the disorder averaged number of contacts with the interface scales at TcT_c like LρL^{\rho} with ρ0.261/νR\rho \sim 0.26 \sim 1/\nu_R .Comment: 9 pages,6 figure

    The Mystery of Two Straight Lines in Bacterial Genome Statistics. Release 2007

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    In special coordinates (codon position--specific nucleotide frequencies) bacterial genomes form two straight lines in 9-dimensional space: one line for eubacterial genomes, another for archaeal genomes. All the 348 distinct bacterial genomes available in Genbank in April 2007, belong to these lines with high accuracy. The main challenge now is to explain the observed high accuracy. The new phenomenon of complementary symmetry for codon position--specific nucleotide frequencies is observed. The results of analysis of several codon usage models are presented. We demonstrate that the mean--field approximation, which is also known as context--free, or complete independence model, or Segre variety, can serve as a reasonable approximation to the real codon usage. The first two principal components of codon usage correlate strongly with genomic G+C content and the optimal growth temperature respectively. The variation of codon usage along the third component is related to the curvature of the mean-field approximation. First three eigenvalues in codon usage PCA explain 59.1%, 7.8% and 4.7% of variation. The eubacterial and archaeal genomes codon usage is clearly distributed along two third order curves with genomic G+C content as a parameter.Comment: Significantly extended version with new data for all the 348 distinct bacterial genomes available in Genbank in April 200

    Endometrial carcinoma: molecular alterations involved in tumor development and progression

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    In the western world, endometrial carcinoma (EC) is the most common cancer of the female genital tract. The annual incidence has been estimated at 10-20 per 100 000 women. Two clinicopathological variants are recognized: the estrogen related (type I, endometrioid) and the non-estrogen related (type II, non-endometrioid).The clinicopathological differences are paralleled by specific genetic alterations, with type I showing microsatellite instability and mutations in phosphatase and tensin homologue deleted on chromosome 70, PIK3CA, K-RAS and CTNNB1 (beta-catenin), and type II exhibiting TP53 mutations and chromosomal instability. Some non-endometrioid carcinomas probably arise from pre-existing endometrioid carcinomas as a result of tumor progression and, not surprisingly, some tumors exhibit combined or mixed features at the clinical, pathological and molecular levels. In EC, apoptosis resistance may have a role in tumor progression. Understanding pathogenesis at the molecular level is essential in identifying biomarkers for successful targeted therapies. In this review, the genetic changes of endometrial carcinogenesis are discussed in the light of the morphological features of the tumors and their precursors

    Correctly validating results from single molecule data: the case of stretched exponential decay in the catalytic activity of single lipase B molecules

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    The question of how to validate and interpret correctly the waiting time probability density functions (WT-PDFs) from single molecule data is addressed. It is shown by simulation that when a stretched exponential WT-PDF, with a stretched exponent alfa and a time scale parameter tau, generates the off periods of a two-state trajectory, a reliable recovery of the input WT-PDF from the trajectory is obtained even when the bin size used to define the trajectory, dt, is much larger than the parameter tau. This holds true as long as the first moment of the WT-PDF is much larger than dt. Our results validate the results in an earlier study of the activity of single Lipase B molecules and disprove recent related critique

    Local Cooperativity Mechanism in the DNA Melting Transition

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    We propose a new statistical mechanics model for the melting transition of DNA. Base pairing and stacking are treated as separate degrees of freedom, and the interplay between pairing and stacking is described by a set of local rules which mimic the geometrical constraints in the real molecule. This microscopic mechanism intrinsically accounts for the cooperativity related to the free energy penalty of bubble nucleation. The model describes both the unpairing and unstacking parts of the spectroscopically determined experimental melting curves. Furthermore, the model explains the observed temperature dependence of the effective thermodynamic parameters used in models of the nearest neighbor (NN) type. We compute the partition function for the model through the transfer matrix formalism, which we also generalize to include non local chain entropy terms. This part introduces a new parametrization of the Yeramian-like transfer matrix approach to the Poland-Scheraga description of DNA melting. The model is exactly solvable in the homogeneous thermodynamic limit, and we calculate all observables without use of the grand partition function. As is well known, models of this class have a first order or continuous phase transition at the temperature of complete strand separation depending on the value of the exponent of the bubble entropy.Comment: Extended version of Phys. Rev. E pape

    ATP-Sensitive Potassium Channels Exhibit Variance in the Number of Open Channels below the Limit Predicted for Identical and Independent Gating

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    In small cells containing small numbers of ion channels, noise due to stochastic channel opening and closing can introduce a substantial level of variability into the cell's membrane potential. Negatively cooperative interactions that couple a channel's gating conformational change to the conformation of its neighbor(s) provide a potential mechanism for mitigating this variability, but such interactions have not previously been directly observed. Here we show that heterologously expressed ATP-sensitive potassium channels generate noise (i.e., variance in the number of open channels) below the level possible for identical and independent channels. Kinetic analysis with single-molecule resolution supports the interpretation that interchannel negative cooperativity (specifically, the presence of an open channel making a closed channel less likely to open) contributes to the decrease in noise. Functional coupling between channels may be important in modulating stochastic fluctuations in cellular signaling pathways
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