Analysis of protein sequence and interaction data for candidate disease gene prediction

Linkage analysis is a successful procedure to associate diseases with specific genomic regions. These regions are often large, containing hundreds of genes, which make experimental methods employed to identify the disease gene arduous and expensive. We present two methods to prioritize candidates for further experimental study: Common Pathway Scanning (CPS) and Common Module Profiling (CMP). CPS is based on the assumption that common phenotypes are associated with dysfunction in proteins that participate in the same complex or pathway. CPS applies network data derived from protein–protein interaction (PPI) and pathway databases to identify relationships between genes. CMP identifies likely candidates using a domain-dependent sequence similarity approach, based on the hypothesis that disruption of genes of similar function will lead to the same phenotype. Both algorithms use two forms of input data: known disease genes or multiple disease loci. When using known disease genes as input, our combined methods have a sensitivity of 0.52 and a specificity of 0.97 and reduce the candidate list by 13-fold. Using multiple loci, our methods successfully identify disease genes for all benchmark diseases with a sensitivity of 0.84 and a specificity of 0.63. Our combined approach prioritizes good candidates and will accelerate the disease gene discovery process.

Obesity and diabetes gene discovery approaches

New treatments are currently required for the common metabolic diseases obesity and type 2 diabetes. The identification of physiological and  biochemical factors that underlie the metabolic disturbances observed in obesity and type 2 diabetes is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the  pathogenesis of these diseases is critical to this process, however  identification of genes that contribute to the risk of developing these diseases represents a significant challenge as obesity and type 2 diabetes are complex diseases with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new targets for obesity and diabetes. To date, DNA-based approaches using candidate gene and genome-wide linkage analysis have had limited success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees using variance components based linkage analysis show great promise in robustly identifying genomic regions associated with the development of obesity and diabetes. RNA-based technologies such as cDNA microarrays have identified many genes differentially expressed in tissues of healthy and diseased subjects. Using a combined approach, we are endeavouring to focus attention on differentially expressed genes located in chromosomal regions previously linked with obesity and / or diabetes. Using this strategy, we have identified Beacon as a potential new target for obesity and diabetes.

Effectively finding relevant web pages from linkage information

This paper presents two hyperlink analysis-based algorithms to find relevant pages for a given Web page (URL). The first algorithm comes from the extended cocitation analysis of the Web pages. It is intuitive and easy to implement. The second one takes advantage of linear algebra theories to reveal deeper relationships among the Web pages and to identify relevant pages more precisely and effectively. The experimental results show the feasibility and effectiveness of the algorithms. These algorithms could be used for various Web applications, such as enhancing Web search. The ideas and techniques in this work would be helpful to other Web-related researches.

A linkage measure framework for the real estate sector

Linkage is one of the most important factors for gaining competitive advantage. Information on linkages is essential to understanding the structure of an economy, which is in turn important in formulating industry policies and business strategies. The hypothetical extraction method is used to measure the linkages by extracting a sector hypothetically from an economic system in the literature. In the previous research, however, the internal linkage (linkage within a sector) and sectoral linkages (linkage between two specific sectors) are ignored, and there is not a comprehensive framework to measure the linkages of a specific sector. Using the recently published Organisation for Economic Co-operation and Development input-output database at constant prices, this paper aims to resolve these two shortcomings and thereby propose a linkage measure framework to explore the linkages between the real estate sector and other sectors from a new angle. The relative and absolute linkages are termed and the total, backward, forward, internal and sectoral linkage indicators are formulated to investigate the linkages of the real estate sector from all directions. Empirical results show an increasing trend of these linkages, which confirms the increasing role of the real estate sector with economic maturity over the examined period. This framework also can be employed in other sectors.

Economic performance analysis of the Australian property sector using input-output tables

The property sector has played an important role with its growing contribution in the national income and employment in the Australian economy. There is an increasing research need in measuring and analysing the economic performance of the Australian property sector at a country level and input-output tables are considered as an appropriate tool. This paper aims to analyse and measure the performance and sectoral linkages of the Australian property sector using the five latest input-output tables compiled by the Australian Bureau of Statistics. Findings suggested that the Australian residential property sector had played a more important role than the commercial sector in the economy. The backward linkage of the residential property sector showed a decreasing economic pull, while that of commercial property presented an upward pattern. Moreover. the Australian property sector showed a medium economic push to the national economy over the examined period. Findings can aid policy makers, the property sector and researchers in evaluating the competitive ability of the property sector in Australia.

Linkage measures of the construction sector using the hypothetical extraction method

The hypothetical extraction method (HEM) is used to extract a sector hypothetically from an economic system and examine the influence of this extraction on other sectors in the economy. Linkage measures based on the HEM become increasingly prominent. However, little construction linkage research applies the HEM. Using the recently published Organisation for Economic Co-operation and Development input-output database at constant prices, this research applies the HEM to the construction sector in order to explore the role of this sector in national economies and the quantitative interdependence between the construction sector and the remaining sectors. The output differences before and after the hypothetical extraction reflect the linkages of the construction sector. Empirical results show a declining trend of the total, backward and forward linkages, which confirms the decreasing role of the construction sector with economic maturity over the examined period from a new angle. Analytical results reveal that the unique nature of the construction sector and multifold external factors are the main reasons for the linkage difference between countries. Moreover, hypothesis-testing results consider statistically that the extraction structures employed in this research are appropriate to analyse the linkages of the construction sector.

Extending construction linkage measures by the consideration of the impact of capital

Construction linkage is a well-established research field. However, a significant limitation in previous linkage research is that the flow of capital goods is not addressed. Using the OECD input-output tables, this research first generates a new input-output model considering capital as an intermediate factor. Using the new model, the construction linkages are recalculated and investigated in order to evaluate further the role of construction in national economies. The findings verify that traditional construction linkages were extremely underestimated in previous research. Furthermore, the effect of capital on construction shows a declining trend over the examined period. After considering the effect of capital, most values and rankings of backward and forward linkages show a decreasing trend, which confirms the declining role of the construction sector with economic maturity.

Factors associated with attributes of internal audit departments : a canonical analysis

This study explores internal audit (IA) practices in selected Ethiopian organizations to identify factors associated with attributes of IA departments. Analytical questionnaire survey responses of 188 IA directors and staff from Ethiopian government ministries, state-owned enterprises and private companies were used. Canonical analysis results show that IA proficiency, scope of IA work and quality of IA planning and execution are higher in organizations where organizational policy authorizing IA is clearly defined, organizational risk exposure is high and internal audit's linkage with external audit is strong. The findings suggest that in organizations that are exposed to high risk, management tends to appreciate IA's assistance in managing risk and thus strengthens IA. Results also suggest the importance of internal and external audit linkages and IA charter (or similar organizational policy) to strengthen IA. The study provides further evidence of differences in IA attributes between public and private sector entities.

The development of 10 novel polymorphic microsatellite markers through next generation sequencing and a preliminary population genetic analysis for the endangered Glenelg spiny crayfish, Euastacus bispinosus

The Glenelg spiny crayfish, Euastacus bispinosus, is an iconic freshwater invertebrate of south eastern Australia and listed as 'endangered' under the Environment Protection and Biodiversity Conservation Act 1999, and 'vulnerable' under the International Union for Conservation of Nature's Red List. The species has suffered major population declines as a result of over-fishing, low environmental flows, the introduction of invasive fish species and habitat degradation. In order to develop an effective conservation strategy, patterns of gene flow, genetic structure and genetic diversity across the species distribution need to be clearly understood. In this study we develop a suite of polymorphic microsatellite markers by next generation sequencing. A total of 15 polymorphic loci were identified and 10 characterized using 22 individuals from the lower Glenelg River. We observed low to moderate genetic variation across most loci (mean number of alleles per locus = 2.80; mean expected heterozygosity = 0.36) with no evidence of individual loci deviating significantly from Hardy-Weinberg equilibrium. Marker independence was confirmed with tests for linkage disequilibrium, and analyses indicated no evidence of null alleles across loci. Individuals from two additional sites (Crawford River, Victoria; Ewens Ponds Conservation Park, South Australia) were genotyped at all 10 loci and a preliminary investigation of genetic diversity and population structure was undertaken. Analyses indicate high levels of genetic differentiation among sample locations (F ST = 0.49), while the Ewens Ponds population is genetically homogeneous, indicating a likely small founder group and ongoing inbreeding. Management actions will be needed to restore genetic diversity in this and possibly other at risk populations. These markers will provide a valuable resource for future population genetic assessments so that an effective framework can be developed for implementing conservation strategies for E. bispinosus.