The Requirements for Ontologies in Medical Data Integration: A Case Study

Evidence-based medicine is critically dependent on three sources of information: a medical knowledge base, the patients medical record and knowledge of available resources, including where appropriate, clinical protocols. Patient data is often scattered in a variety of databases and may, in a distributed model, be held across several disparate repositories. Consequently addressing the needs of an evidence-based medicine community presents issues of biomedical data integration, clinical interpretation and knowledge management. This paper outlines how the Health-e-Child project has approached the challenge of requirements specification for (bio-) medical data integration, from the level of cellular data, through disease to that of patient and population. The approach is illuminated through the requirements elicitation and analysis of Juvenile Idiopathic Arthritis (JIA), one of three diseases being studied in the EC-funded Health-e-Child project.Comment: 6 pages, 1 figure. Presented at the 11th International Database Engineering & Applications Symposium (Ideas2007). Banff, Canada September 200

MEASURING MARKET INTEGRATION IN THE PRESENCE OF TRANSACTION COSTS - A THRESHOLD VECTOR ERROR CORRECTION APPROACH

Applied econometric analyses of market integration based on price data alone have been criticised, because they neglect the role of transaction costs. To meet this objection threshold vector error correction models are used. Threshold models can account for the effects of transaction costs in price transmission without directly relying upon information about these costs, which are often unavailable. Results from threshold models that are based on two thresholds provide results that are economically more intuitive than those obtained from one threshold models. However there is no adequate econometric test for threshold significance in a two-threshold model available so far; such tests are only available for the one threshold model. In this paper a restricted two-threshold model is developed in which the significance of the thresholds can be tested. This model is therefore amenable to economic interpretation and statistical inference. This model is used to estimate market integration on the European pig market.Industrial Organization,

Integrasi Bahasa Inggris ke Bahasa Indonesia Berbasis Media Komunikasi Elektronik Komputer.

This study has two purposes. (1) Describe the design of the development model of English integration theory into Indonesian based on electronic computer communication media. (2) To describe factors causing the integration of English into Indonesian based on electronic computer communication media. This study used descriptive qualitative method. The data in this research is a word that contains the integration of English into Indonesian based electronic communication media computer. Data collection techniques in this study is the method refer and the method of record. The method of referring to the use of language in the computer electronic communication media to identify data about the integration of English into Indonesian language. Record technique used by researchers to record data in the form of words that contain integration of English into Indonesian language based on computer communication media. The results of this study indicate that the design of the development model of English integration theory into Indonesian based electronic computer communication media is grouped into two processes. (1) direct translation and (2) interpretation of concepts. Factors causing the integration of English into Indonesian-based electronic computer communication media is due to (1) the speaker's bilingualism and (2) the development of Science and Technology. Keywords: integration, electronic computer communication media

Multimodal regularised linear models with flux balance analysis for mechanistic integration of omics data

Motivation: High-throughput biological data, thanks to technological advances, have become cheaper to collect, leading to the availability of vast amounts of omic data of different types. In parallel, the in silico reconstruction and modeling of metabolic systems is now acknowledged as a key tool to complement experimental data on a large scale. The integration of these model- and data-driven information is therefore emerging as a new challenge in systems biology, with no clear guidance on how to better take advantage of the inherent multisource and multiomic nature of these data types while preserving mechanistic interpretation. Results: Here, we investigate different regularization techniques for high-dimensional data derived from the integration of gene expression profiles with metabolic flux data, extracted from strain-specific metabolic models, to improve cellular growth rate predictions. To this end, we propose ad-hoc extensions of previous regularization frameworks including group, view-specific and principal component regularization and experimentally compare them using data from 1143 Saccharomyces cerevisiae strains. We observe a divergence between methods in terms of regression accuracy and integration effectiveness based on the type of regularization employed. In multiomic regression tasks, when learning from experimental and model-generated omic data, our results demonstrate the competitiveness and ease of interpretation of multimodal regularized linear models compared to data-hungry methods based on neural networks. Availability and implementation: All data, models and code produced in this work are available on GitHub at https://github.com/Angione-Lab/HybridGroupIPFLasso_pc2Lasso. Supplementary information: Supplementary data are available at Bioinformatics online

Model-based joint visualization of multiple compositional omics datasets

The integration of multiple omics datasets measured on the same samples is a challenging task: data come from heterogeneous sources and vary in signal quality. In addition, some omics data are inherently compositional, e.g. sequence count data. Most integrative methods are limited in their ability to handle covariates, missing values, compositional structure and heteroscedasticity. In this article we introduce a flexible model-based approach to data integration to address these current limitations: COMBI. We combine concepts, such as compositional biplots and log-ratio link functions with latent variable models, and propose an attractive visualization through multiplots to improve interpretation. Using real data examples and simulations, we illustrate and compare our method with other data integration techniques. Our algorithm is available in the R-package combi

The application of remote sensing to identify and measure sealed soil and vegetated surfaces in urban environments

Soil is an important non-renewable source. Its protection and allocation is critical to sustainable development goals. Urban development presents an important drive of soil loss due to sealing over by buildings, pavements and transport infrastructure. Monitoring sealed soil surfaces in urban environments is gaining increasing interest not only for scientific research studies but also for local planning and national authorities. The aim of this research was to investigate the extent to which automated classification methods can detect soil sealing in UK urban environments, by remote sensing. The objectives include development of object-based classification methods, using two types of earth observation data, and evaluation by comparison with manual aerial photo interpretation techniques. Four sample areas within the city of Cambridge were used for the development of an object-based classification model. The acquired data was a true-colour aerial photography (0.125 m resolution) and a QuickBird satellite imagery (2.8 multi-spectral resolution). The classification scheme included the following land cover classes: sealed surfaces, vegetated surfaces, trees, bare soil and rail tracks. Shadowed areas were also identified as an initial class and attempts were made to reclassify them into the actual land cover type. The accuracy of the thematic maps was determined by comparison with polygons derived from manual air-photo interpretation; the average overall accuracy was 84%. The creation of simple binary maps of sealed vs. vegetated surfaces resulted in a statistically significant accuracy increase to 92%. The integration of ancillary data (OS MasterMap) into the object-based model did not improve the performance of the model (overall accuracy of 91%). The use of satellite data in the object-based model gave an overall accuracy of 80%, a 7% decrease compared to the aerial photography. Future investigation will explore whether the integration of elevation data will aid to discriminate features such as trees from other vegetation types. The use of colour infrared aerial photography should also be tested. Finally, the application of the object- based classification model into a different study area would test its transferability

How Integrated are World Capital Markets? Some New Tests

This paper present some new empirical evidence on the extent of world capital-market integration. The first set of tests carried out uses data from different countries to compare internationally expected marginal rates of substitution between consumption on different dates. If residents of different countries have access to a nominally risk-free bond denominated in dollars, say, their common expected marginal rate of substitution of future for present dollars should equal the gross nominal return on dollar bonds. Tests of the international equality of expected marginal substitution rates yield evidence consistent with a substantial degree of international capital-market integration after, but not before, 1973. These tests are naturally based on a particular model of intertemporal consumption choice, but direct estimation of the inter-country relationships implied by that model lends support to its assumptions. These last findings are relevant to the current debate in macroeconomics about the role of intertemporal substitution. The second set of tests conducted in this paper concerns correlations between countries' saving and investment rates. For a sample often countries, correlations between annual changes in saving and investment rates over the period 1948-1984 look quite similar to those found in quarterly data. Surprisingly, however, the correlation coefficients are often lower before the mid-1960s than afterward This finding throws further doubt on the interpretation of saving-investment correlation coefficients as structural parameters reflecting the response of domestic investment to shifts in national saving.