Suffolk University

About: Suffolk University is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Sugar beet. The organization has 6462 authors who have published 9321 publications receiving 235328 citations.

THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Enzymes.

Abstract: The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15542. Enzymes are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

Dependence Structure and Extreme Comovements in International Equity and Bond Markets

Abstract: Common negative extreme variations in returns are prevalent in international equity markets. This has been widely documented with statistical tools such as exceedance correlation, extreme value theory, and Gaussian bivariate GARCH or regime-switching models. We point to limits of these tools to characterize extreme dependence and propose an alternative regime-switching copula model that includes one normal regime in which dependence is symmetric and a second regime characterized by asymmetric dependence. We apply this model to international equity and bond markets, to allow for inter-market movements. Empirically, we find that dependence between international assets of the same type is strong in both regimes, especially in the asymmetric one, but weak between equities and bonds, even in the same country.

Managing Data Quality in Dynamic Decision Environments: An Information Product Approach

Abstract: Large data volumes, widely distributed data sources, and multiple stakeholders characterize typical e-business settings. Mobile and wireless technologies have further increased data volumes, further distributed the data sources, while permitting access to data anywhere, anytime. Such environments empower and necessitate decision-makers to act/react quicker to all decision-tasks including mission-critical ones. Decision-support in such environments demands efficient data quality management. This paper presents a framework for managing data quality in such environments using the information product approach. It includes a modeling technique to explicitly represent the manufacture of an information product, quality dimensions and methods to compute data quality of the product at any stage in the manufacture, and a set of capabilities to comprehensively manage data quality and implement total data quality management. The paper also posits the notion of a virtual business environment to support dynamic decision-making and describes the role of the data quality framework in this environment.