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

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

The DLV System for Knowledge Representation and Reasoning

This paper presents the DLV system, which is widely considered the state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free disjunctive logic programs (also known as disjunctive datalog), extended by weak constraints, which are a powerful tool to express optimization problems. We then illustrate the usage of DLV as a tool for knowledge representation and reasoning, describing a new declarative programming methodology which allows one to encode complex problems (up to $\Delta^P_3$-complete problems) in a declarative fashion. On the foundational side, we provide a detailed analysis of the computational complexity of the language of DLV, and by deriving new complexity results we chart a complete picture of the complexity of this language and important fragments thereof. Furthermore, we illustrate the general architecture of the DLV system which has been influenced by these results. As for applications, we overview application front-ends which have been developed on top of DLV to solve specific knowledge representation tasks, and we briefly describe the main international projects investigating the potential of the system for industrial exploitation. Finally, we report about thorough experimentation and benchmarking, which has been carried out to assess the efficiency of the system. The experimental results confirm the solidity of DLV and highlight its potential for emerging application areas like knowledge management and information integration.Comment: 56 pages, 9 figures, 6 table

A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations

Abstract Background Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. Methods We used age standardised incidence ratios (SIRs) of esophageal cancer (EC) from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1) Poisson regression with agglomeration-specific nonspatial random effects; (2) Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC), Akaike's information criterion (AIC) and adjusted pseudo R2, were used for model comparison. Results A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. Conclusions The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.</p

The Consolidation of the White Southern Congressional Vote

This article explores the initial desertion and continued realignment of about one-sixth of the white voters in the South who, until 1994, stood by Democratic congressional candidates even as they voted for Republican presidential nominees. Prior to 1994, a sizable share of the white electorate distinguished between Democratic congressional and presidential candidates; since 1994 that distinction has been swept away. In 1992, a majority of white southern voters was casting their ballot for the Democratic House nominee; by 1994, the situation was reversed and 64 percent cast their ballot for the Republican. Virtually all categories of voters increased their support of Republican congressional candidates in 1994 and the following elections further cement GOP congressional support in the South. Subsequent elections are largely exercises in partisanship, as the congressional votes mirror party preferences. Republicans pull nearly all GOP identifiers, most independents, and a sizeable minority of Democratic identifiers. Democrats running for Congress no longer convince voters that they are different from their party’s presidential standard bearers—a group that has consistently been judged unacceptable to overwhelming proportions of the southern white electorate.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

The effects of economic deprivation on psychological well-being among the working population of Switzerland

BACKGROUND: The association between poverty and mental health has been widely investigated. There is, however, limited evidence of mental health implications of working poverty, despite its representing a rapidly expanding segment of impoverished populations in many developed nations. In this study, we examined whether working poverty in Switzerland, a country with substantial recent growth among the working poor, was correlated with two dependent variables of interest: psychological health and unmet mental health need. METHODS: This cross-sectional study used data drawn from the first 3 waves (1999–2001) of the Swiss Household Panel, a nationally representative sample of the permanent resident population of Switzerland. The study sample comprised 5453 subjects aged 20–59 years. We used Generalized Estimating Equation models to investigate the association between working poverty and psychological well-being; we applied logistic regression models to analyze the link between working poverty and unmet mental health need. Working poverty was represented by dummy variables indicating financial deficiency, restricted standard of living, or both conditions. RESULTS: After controlling other factors, restricted standard of living was significantly (p < .001) negatively correlated with psychological well-being; it was also associated with approximately 50% increased risk of unmet mental health need (OR = 1.55; 95% CI 1.17 – 2.06). CONCLUSION: The findings of this study contribute to our understanding of the potential psychological impact of material deprivation on working Swiss citizens. Such knowledge may aid in the design of community intervention programs to help reduce the individual and societal burdens of poverty in Switzerland

A Population Proportion approach for ranking differentially expressed genes

<p>Abstract</p> <p>Background</p> <p>DNA microarrays are used to investigate differences in gene expression between two or more classes of samples. Most currently used approaches compare mean expression levels between classes and are not geared to find genes whose expression is significantly different in only a subset of samples in a class. However, biological variability can lead to situations where key genes are differentially expressed in only a subset of samples. To facilitate the identification of such genes, a new method is reported.</p> <p>Methods</p> <p>The key difference between the Population Proportion Ranking Method (PPRM) presented here and almost all other methods currently used is in the quantification of variability. PPRM quantifies variability in terms of inter-sample ratios and can be used to calculate the relative merit of differentially expressed genes with a specified difference in expression level between at least some samples in the two classes, which at the same time have lower than a specified variability within each class.</p> <p>Results</p> <p>PPRM is tested on simulated data and on three publicly available cancer data sets. It is compared to the t test, PPST, COPA, OS, ORT and MOST using the simulated data. Under the conditions tested, it performs as well or better than the other methods tested under low intra-class variability and better than t test, PPST, COPA and OS when a gene is differentially expressed in only a subset of samples. It performs better than ORT and MOST in recognizing non differentially expressed genes with high variability in expression levels across all samples. For biological data, the success of predictor genes identified in appropriately classifying an independent sample is reported.</p

Citizenship Norms in Eastern Europe

Research on Eastern Europe stresses the weakness of its civil society and the lack of political and social involvement, neglecting the question: What do people themselves think it means to be a good citizen? This study looks at citizens’ definitions of good citizenship in Poland, Slovenia, the Czech Republic and Hungary, using 2002 European Social Survey data. We investigate mean levels of civic mindedness in these countries and perform regression analyses to investigate whether factors traditionally associated with civic and political participation are also correlated with citizenship norms across Eastern Europe. We show that mean levels of civic mindedness differ significantly across the four Eastern European countries. We find some support for theories on civic and political participation when explaining norms of citizenship, but also demonstrate that individual-level characteristics are differently related to citizenship norms across the countries of our study. Hence, our findings show that Eastern Europe is not a monolithic and homogeneous bloc, underscoring the importance of taking the specificities of countries into account

Gene expression throughout a vertebrate's embryogenesis

Abstract Background Describing the patterns of gene expression during embryonic development has broadened our understanding of the processes and patterns that define morphogenesis. Yet gene expression patterns have not been described throughout vertebrate embryogenesis. This study presents statistical analyses of gene expression during all 40 developmental stages in the teleost Fundulus heteroclitus using four biological replicates per stage. Results Patterns of gene expression for 7,000 genes appear to be important as they recapitulate developmental timing. Among the 45% of genes with significant expression differences between pairs of temporally adjacent stages, significant differences in gene expression vary from as few as five to more than 660. Five adjacent stages have disproportionately more significant changes in gene expression (&gt; 200 genes) relative to other stages: four to eight and eight to sixteen cell stages, onset of circulation, pre and post-hatch, and during complete yolk absorption. The fewest differences among adjacent stages occur during gastrulation. Yet, at stage 16, (pre-mid-gastrulation) the largest number of genes has peak expression. This stage has an over representation of genes in oxidative respiration and protein expression (ribosomes, translational genes and proteases). Unexpectedly, among all ribosomal genes, both strong positive and negative correlations occur. Similar correlated patterns of expression occur among all significant genes. Conclusions These data provide statistical support for the temporal dynamics of developmental gene expression during all stages of vertebrate development