952 resultados para Opportunity discovery and exploitation


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Tese de dout., Ciências e Tecnologia das Pescas, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2005

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This work aimed to contribute to drug discovery and development (DDD) for tauopathies, while expanding our knowledge on this group of neurodegenerative disorders, including Alzheimer’s disease (AD). Using yeast, a recognized model for neurodegeneration studies, useful models were produced for the study of tau interaction with beta-amyloid (Aβ), both AD hallmark proteins. The characterization of these models suggests that these proteins co-localize and that Aβ1-42, which is toxic to yeast, is involved in tau40 phosphorylation (Ser396/404) via the GSK-3β yeast orthologue, whereas tau seems to facilitate Aβ1-42 oligomerization. The mapping of tau’s interactome in yeast, achieved with a tau toxicity enhancer screen using the yeast deletion collection, provided a novel framework, composed of 31 genes, to identify new mechanisms associated with tau pathology, as well as to identify new drug targets or biomarkers. This genomic screen also allowed to select the yeast strain mir1Δ-tau40 for development of a new GPSD2TM drug discovery screening system. A library of unique 138 marine bacteria extracts, obtained from the Mid-Atlantic Ridge hydrothermal vents, was screened with mir1Δ-tau40. Three extracts were identified as suppressors of tau toxicity and constitute good starting points for DDD programs. mir1Δ strain was sensitive to tau toxicity, relating tau pathology with mitochondrial function. SLC25A3, the human homologue of MIR1, codes for the mitochondrial phosphate carrier protein (PiC). Resorting to iRNA, SLC25A3 expression was silenced in human neuroglioma cells, as a first step towards the engineering of a neural model for replicating the results obtained in yeast. This model is essential to understand the mechanisms of tau toxicity at the mitochondrial level and to validate PiC as a relevant drug target. The set of DDD tools here presented will foster the development of innovative and efficacious therapies, urgently needed to cope with tau-related disorders of high human and social-economic impact.

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Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p < 5 × 10(-8)) for serum albumin (HPN-SCN1B, GCKR-FNDC4, SERPINF2-WDR81, TNFRSF11A-ZCCHC2, FRMD5-WDR76, and RPS11-FCGRT, in up to 53,190 European-ancestry and 9,380 Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease.

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In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

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Excavations at the Pre-Pottery Neolithic site of WF16 in the Southern Levant produced an archaeobotanical assemblage constituted by plant macro-fossils and wood charcoal. As with all such assemblages, its species composition will most likely provide a biased reflection of those within the Neolithic woodland that had been exploited owing to cultural selection and differential preservation. As a means of facilitating its interpretation, a survey was undertaken of a relatively undisturbed patch of gallery woodland associated with a permanent water course at Hammam Adethni, approximately four kilometres south-east of WF16. The substantial overlap of the species within this woodland and those in the archaeobotanical assemblage suggests that this present-day woodland provides an analogue for that of the Neolithic and may therefore indicate what other plant resources the inhabitants of WF16 may have exploited, but which have left no archaeological trace. The interpretation of the results is supported by a comparative study of wood charcoal from present-day Bedouin hearths in Wadi Faynan.

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The first haploid angiosperm, a dwarf form of cotton with half the normal chromosome complement, was discovered in 1920, and in the ninety years since then such plants have been identified in many other species. They can occur either spontaneously or can be induced by modified pollination methods in vivo, or by in vitro culture of immature male or female gametophytes. Haploids represent an immediate, one-stage route to homozygous diploids and thence to F(1) hybrid production. The commercial exploitation of heterosis in such F(1) hybrids leads to the development of hybrid seed companies and subsequently to the GM revolution in agriculture. This review describes the range of techniques available for the isolation or induction of haploids and discusses their value in a range of areas, from fundamental research on mutant isolation and transformation, through to applied aspects of quantitative genetics and plant breeding. It will also focus on how molecular methods have been used recently to explore some of the underlying aspects of this fascinating developmental phenomenon.

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Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

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There are three key components for developing a metadata system: a container structure laying out the key semantic issues of interest and their relationships; an extensible controlled vocabulary providing possible content; and tools to create and manipulate that content. While metadata systems must allow users to enter their own information, the use of a controlled vocabulary both imposes consistency of definition and ensures comparability of the objects described. Here we describe the controlled vocabulary (CV) and metadata creation tool built by the METAFOR project for use in the context of describing the climate models, simulations and experiments of the fifth Coupled Model Intercomparison Project (CMIP5). The CV and resulting tool chain introduced here is designed for extensibility and reuse and should find applicability in many more projects.

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The notion that wetlands are among the most productive environments in the world is widely quoted, but its relationship with the exploitation of wetland ecosystems during the prehistoric and early historic period has been the subject of few investigations. The current paper discusses the primary production of different wetland habitats and its relationship to the resource potential of these habitats and their actual exploitation, using recent results from the Humber Wetlands Survey. It is argued that during the early Holocene, wetland landscapes were central to the subsistence economy and that a clear association exists between the primary productivity of wetlands and the intensity of exploitation. With the introduction of agriculture, however, wetland habitats become increasingly peripheral to the economy.

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This paper examines the determinants of cross-platform arbitrage profits. We develop a structural model that enables us to decompose the likelihood of an arbitrage opportunity into three distinct factors: the fixed cost to trade the opportunity, the level at which one of the platforms delays a price update and the impact of the order flow on the quoted prices (inventory and asymmetric information effects). We then investigate the predictions from the theoretical model for the European Bond market with the estimation of a probit model. Our main finding is that the results found in the empirical part corroborate strongly the predictions from the structural model. The event of a cross market arbitrage opportunity has a certain degree of predictability where an optimal ex ante scenario is represented by a low level of spreads on both platforms, a time of the day close to the end of trading hours and a high volume of trade.

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Prior to deforestation, So Paulo State had 79,000 km(2) covered by Cerrado (Brazilian savanna) physiognomies, but today less than 8.5% of this biodiversity hotspot remains, mostly in private lands. The global demand for agricultural goods has imposed strong pressure on natural areas, and the economic decisions of agribusiness managers are crucial to the fate of Cerrado domain remaining areas (CDRA) in Brazil. Our aim was to investigate the effectiveness of Brazilian private protected areas policy, and to propose a feasible alternative to promote CDRA protection. This article assessed the main agribusiness opportunity costs for natural areas preservation: the land use profitability and the arable land price. The CDRA percentage and the opportunity costs were estimated for 349 municipal districts of So Paulo State through secondary spatial data and profitability values of 38 main agricultural products. We found that Brazilian private protected areas policy fails to preserve CDRA, although the values of non-compliance fines were higher than average opportunity costs. The scenario with very restrictive laws on private protected areas and historical high interest rates allowed us to conceive a feasible cross compliance proposal to improve environmental and agricultural policies.

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Summarizes previous research on the investment opportunity set (IOS) using price-based and investment-based proxies and variance measures; and develops hypotheses on the relationship between IOS, debt/equity ratios and dividend policies. Tests them on 1990-1998 data from listed Australian companies and explains the methodology, which builds on Gover and Gover (1993) by including more recent proxy variables. Finds no significant results from low growth firms, although some high growth firms show lower debt/equity ratios and dividends. Questions the robustness of existing IOS proxies in the Australian context and calls for further research.