2,826 research outputs found

    Justice Stephen G. Breyer

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    Regulatory activity revealed by dynamic correlations in gene expression noise

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    Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or 'noise', in gene expression propagate through active, but not inactive, regulatory links^(1,2). Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, 'extrinsic', noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits

    Staircase polygons: moments of diagonal lengths and column heights

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    We consider staircase polygons, counted by perimeter and sums of k-th powers of their diagonal lengths, k being a positive integer. We derive limit distributions for these parameters in the limit of large perimeter and compare the results to Monte-Carlo simulations of self-avoiding polygons. We also analyse staircase polygons, counted by width and sums of powers of their column heights, and we apply our methods to related models of directed walks.Comment: 24 pages, 7 figures; to appear in proceedings of Counting Complexity: An International Workshop On Statistical Mechanics And Combinatorics, 10-15 July 2005, Queensland, Australi

    Validation of Claims Data Algorithms to Identify Nonmelanoma Skin Cancer

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    Health maintenance organization (HMO) administrative databases have been used as sampling frames for ascertaining nonmelanoma skin cancer (NMSC). However, because of the lack of tumor registry information on these cancers, these ascertainment methods have not been previously validated. NMSC cases arising from patients served by a staff model medical group and diagnosed between 1 January 2007 and 31 December 2008 were identified from claims data using three ascertainment strategies. These claims data cases were then compared with NMSC identified using natural language processing (NLP) of electronic pathology reports (EPRs), and sensitivity, specificity, positive and negative predictive values were calculated. Comparison of claims data–ascertained cases with the NLP demonstrated sensitivities ranging from 48 to 65% and specificities from 85 to 98%, with ICD-9-CM ascertainment demonstrating the highest case sensitivity, although the lowest specificity. HMO health plan claims data had a higher specificity than all-payer claims data. A comparison of EPR and clinic log registry cases showed a sensitivity of 98% and a specificity of 99%. Validation of administrative data to ascertain NMSC demonstrates respectable sensitivity and specificity, although NLP ascertainment was superior. There is a substantial difference in cases identified by NLP compared with claims data, suggesting that formal surveillance efforts should be considered

    Pure point diffraction and cut and project schemes for measures: The smooth case

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    We present cut and project formalism based on measures and continuous weight functions of sufficiently fast decay. The emerging measures are strongly almost periodic. The corresponding dynamical systems are compact groups and homomorphic images of the underlying torus. In particular, they are strictly ergodic with pure point spectrum and continuous eigenfunctions. Their diffraction can be calculated explicitly. Our results cover and extend corresponding earlier results on dense Dirac combs and continuous weight functions with compact support. They also mark a clear difference in terms of factor maps between the case of continuous and non-continuous weight functions.Comment: 30 page

    Rigorous results on spontaneous symmetry breaking in a one-dimensional driven particle system

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    We study spontaneous symmetry breaking in a one-dimensional driven two-species stochastic cellular automaton with parallel sublattice update and open boundaries. The dynamics are symmetric with respect to interchange of particles. Starting from an empty initial lattice, the system enters a symmetry broken state after some time T_1 through an amplification loop of initial fluctuations. It remains in the symmetry broken state for a time T_2 through a traffic jam effect. Applying a simple martingale argument, we obtain rigorous asymptotic estimates for the expected times ~ L ln(L) and ln() ~ L, where L is the system size. The actual value of T_1 depends strongly on the initial fluctuation in the amplification loop. Numerical simulations suggest that T_2 is exponentially distributed with a mean that grows exponentially in system size. For the phase transition line we argue and confirm by simulations that the flipping time between sign changes of the difference of particle numbers approaches an algebraic distribution as the system size tends to infinity.Comment: 23 pages, 7 figure
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