gap: Genetic Analysis Package

A preliminary attempt at collecting tools and utilities for genetic data as an R package called gap is described. Genomewide association is then described as a specific example, linking the work of Risch and Merikangas (1996), Long and Langley (1997) for family-based and population-based studies, and the counterpart for case-cohort design established by Cai and Zeng (2004). Analysis of staged design as outlined by Skol et al. (2006) and associate methods are discussed. The package is flexible, customizable, and should prove useful to researchers especially in its application to genomewide association studies.

gap: Genetic Analysis Package

A preliminary attempt at collecting tools and utilities for genetic data as an R package called gap is described. Genomewide association is then described as a specific example, linking the work of Risch and Merikangas (1996), Long and Langley (1997) for family-based and population-based studies, and the counterpart for case-cohort design established by Cai and Zeng (2004). Analysis of staged design as outlined by Skol et al. (2006) and associate methods are discussed. The package is flexible, customizable, and should prove useful to researchers especially in its application to genomewide association studies

Bi- and tri-dentate imino-based iron and cobalt pre-catalysts for ethylene oligo-/polymerization

Recent progress on the use of iron and cobalt complex pre-catalysts for ethylene reactivity is reviewed. The review is organized in terms of the denticity of the chelate ligands employed, with particular reference to the influence of the ligand frameworks and their substituents on the catalytic performance for ethylene oligomerization/polymerization catalysis. The majority of the systems bear tri-dentate ligation at the iron/cobalt centre, though it is clear that bi-dentate iron/cobalt complex pre-catalysts have also attracted significant attention. Such systems produce in most cases highly linear products ranging from oligomeric α-olefins to high molecular weight polyethylene, and as such are promising candidates for both academic and industrial considerations

Differential quadrature solutions to dynamic response of cylindrical shell subjected to thermal shock

The dynamic response of the cylindrical shell subjected to thermal shock is investigated. Based on the classical shell theory, dynamic governing equations of thin shell with the simply supported edges under thermal shock are derived by using Hamilton principle. The temperature field, the thermal axial force and the thermal bending moment are obtained in combination of Laplace transform and series expansion when the internal surface of shell is subjected to thermal shock loading. Considering of the axisymmetric deformation, the transient displacements and thermal stresses of the shell are obtained using the differential quadrature method. The effects of the thermal shock load and the geometrical parameters of the cylindrical shell on the central deflection, the axial displacement, the bending configurations and the transient thermal stresses are analyzed

Mixed Modeling with Whole Genome Data

Objective. We consider the need for a modeling framework for related individuals and various sources of variations. The relationships could either be among relatives in families or among unrelated individuals in a general population with cryptic relatedness; both could be refined or derived with whole genome data. As with variations they can include oliogogenes, polygenes, single nucleotide polymorphism (SNP), and covariates. Methods. We describe mixed models as a coherent theoretical framework to accommodate correlations for various types of outcomes in relation to many sources of variations. The framework also extends to consortium meta-analysis involving both population-based and family-based studies. Results. Through examples we show that the framework can be furnished with general statistical packages whose great advantage lies in simplicity and exibility to study both genetic and environmental effects. Areas which require further work are also indicated. Conclusion. Mixed models will play an important role in practical analysis of data on both families and unrelated individuals when whole genome information is available

The research for effect of aspects extraction of Chinese commodity comments on supervised learning methods

Abstract With the advent of Web 2.0, there are more and more websites for shopping. These websites often allow customers make comments of the commodity which they have purchased. Therefore, three is an increasing number of online reviews. More importantly, these reviews contain a mass of sentiment. The sentiment is meaningful for merchants and customers. This paper focuses on the extraction of aspects of online review of products. We will use Supervised Learning methods to extract aspects of online review of products. Through the experiment of this paper, we found that Machine Learning can be used for aspects extraction of Chinese online review of products. Using ME and presence character representation can achieve 85.6% accuracy

Selecting cases from nuclear families for case-control association analysis

We examine the efficiency of a number of schemes to select cases from nuclear families for case-control association analysis using the Genetic Analysis Workshop 14 simulated dataset. We show that with this simulated dataset comparing all affected siblings with unrelated controls is considerably more powerful than all of the other approaches considered. We find that the test statistic is increased by almost 3-fold compared to the next best sampling schemes of selecting all affected sibs only from families with affected parents (AF(aff)), one affected sib with most evidence of allele-sharing from each family (SF), and all affected sibs from families with evidence for linkage (AF(L)). We consider accounting for biological relatedness of samples in the association analysis to maintain the correct type I error. We also discuss the relative efficiencies of increasing the ratio of unrelated cases to controls, methods to confirm associations and issues to consider when applying our conclusions to other complex disease datasets