Geographically intelligent disclosure control for flexible aggregation of census data

This paper describes a geographically intelligent approach to disclosure control for protecting flexibly aggregated census data. Increased analytical power has stimulated user demand for more detailed information for smaller geographical areas and customized boundaries. Consequently it is vital that improved methods of statistical disclosure control are developed to protect against the increased disclosure risk. Traditionally methods of statistical disclosure control have been aspatial in nature. Here we present a geographically intelligent approach that takes into account the spatial distribution of risk. We describe empirical work illustrating how the flexibility of this new method, called local density swapping, is an improved alternative to random record swapping in terms of risk-utility

An Effectiveness Review of Section 404 of the Sarbanes Oxley Act (2002)

The accounting scandals that occurred in the early 2000s launched the current day regulations set fourth in the Sarbanes Oxley Act. The Sarbanes Oxley Act is comprised of several titles, all aimed to help eliminate financial accounting errors and the potential of fraud. Within this piece of legislation, there is one section that has created a lot of discussion. Section 404, which discusses the way in which disclosures of internal control deficiencies are handled, is the topic of this paper. In addition to a literature review of a research paper written by Sarah Rice and David Weber, this paper will look at different elements to see if this section of the Sarbanes Oxley Act has changed the regulatory environment. Through comparative studies, this paper is aimed to see if the legislation created to stop these financial scandals from happening, was successful and effective

On the hierarchical classification of G Protein-Coupled Receptors

Motivation: G protein-coupled receptors (GPCRs) play an important role in many physiological systems by transducing an extracellular signal into an intracellular response. Over 50% of all marketed drugs are targeted towards a GPCR. There is considerable interest in developing an algorithm that could effectively predict the function of a GPCR from its primary sequence. Such an algorithm is useful not only in identifying novel GPCR sequences but in characterizing the interrelationships between known GPCRs. Results: An alignment-free approach to GPCR classification has been developed using techniques drawn from data mining and proteochemometrics. A dataset of over 8000 sequences was constructed to train the algorithm. This represents one of the largest GPCR datasets currently available. A predictive algorithm was developed based upon the simplest reasonable numerical representation of the protein's physicochemical properties. A selective top-down approach was developed, which used a hierarchical classifier to assign sequences to subdivisions within the GPCR hierarchy. The predictive performance of the algorithm was assessed against several standard data mining classifiers and further validated against Support Vector Machine-based GPCR prediction servers. The selective top-down approach achieves significantly higher accuracy than standard data mining methods in almost all cases

BioWorkbench: A High-Performance Framework for Managing and Analyzing Bioinformatics Experiments

Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require high-performance computing (HPC) techniques and can benefit from specialized technologies such as Scientific Workflow Management Systems (SWfMS) and databases. In this work, we present BioWorkbench, a framework for managing and analyzing bioinformatics experiments. This framework automatically collects provenance data, including both performance data from workflow execution and data from the scientific domain of the workflow application. Provenance data can be analyzed through a web application that abstracts a set of queries to the provenance database, simplifying access to provenance information. We evaluate BioWorkbench using three case studies: SwiftPhylo, a phylogenetic tree assembly workflow; SwiftGECKO, a comparative genomics workflow; and RASflow, a RASopathy analysis workflow. We analyze each workflow from both computational and scientific domain perspectives, by using queries to a provenance and annotation database. Some of these queries are available as a pre-built feature of the BioWorkbench web application. Through the provenance data, we show that the framework is scalable and achieves high-performance, reducing up to 98% of the case studies execution time. We also show how the application of machine learning techniques can enrich the analysis process

The Commons Concept and Intellectual Property Rights Regime: Whither Plant Genetic Resources and Traditional Knowledge?

[Excerpt] The classification of plant genetic resources (PGRs) as the common heritage of humankind continues to generate controversies. The debate is between developing countries that are the primary sources of these resources and industrialized, biotechnologically advanced countries that appropriate and utilize PGRs as raw materials for various commercial products, such as medicine, seed variety, or pesticides. Scholars of diverse backgrounds express various opinions on whether PGRs obtained from plants found within a territory of a sovereign state should properly be designated “common heritage of humankind” or regarded as part of the “commons,” and therefore freely accessible. The debate also extends to and challenges the status of traditional knowledge on the uses of PGRs. The dominant but not necessarily the correct view is that such knowledge is information in the public domain, incapable of private ownership or control