942 resultados para Knowledge Discovery Database


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Sickle Cell Disease (SCD) is one of the most prevalent hematological diseases in the world. Despite the immense progress in molecular knowledge about SCD in last years few therapeutical sources are currently available. Nowadays the treatment is performed mainly with drugs such as hydroxyurea or other fetal hemoglobin inducers and chelating agents. This review summarizes current knowledge about the treatment and the advancements in drug design in order to discover more effective and safe drugs. Patient monitoring methods in SCD are also discussed. © 2011 Bentham Science Publishers Ltd.

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A significant set of information stored in different databases around the world, can be shared through peer-topeer databases. With that, is obtained a large base of knowledge, without the need for large investments because they are used existing databases, as well as the infrastructure in place. However, the structural characteristics of peer-topeer, makes complex the process of finding such information. On the other side, these databases are often heterogeneous in their schemas, but semantically similar in their content. A good peer-to-peer databases systems should allow the user access information from databases scattered across the network and receive only the information really relate to your topic of interest. This paper proposes to use ontologies in peer-to-peer database queries to represent the semantics inherent to the data. The main contribution of this work is enable integration between heterogeneous databases, improve the performance of such queries and use the algorithm of optimization Ant Colony to solve the problem of locating information on peer-to-peer networks, which presents an improve of 18% in results. © 2011 IEEE.

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The development of new technologies that use peer-to-peer networks grows every day, with the object to supply the need of sharing information, resources and services of databases around the world. Among them are the peer-to-peer databases that take advantage of peer-to-peer networks to manage distributed knowledge bases, allowing the sharing of information semantically related but syntactically heterogeneous. However, it is a challenge to ensure the efficient search for information without compromising the autonomy of each node and network flexibility, given the structural characteristics of these networks. On the other hand, some studies propose the use of ontology semantics by assigning standardized categorization of information. The main original contribution of this work is the approach of this problem with a proposal for optimization of queries supported by the Ant Colony algorithm and classification though ontologies. The results show that this strategy enables the semantic support to the searches in peer-to-peer databases, aiming to expand the results without compromising network performance. © 2011 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Thanks to the Chandra and XMM–Newton surveys, the hard X-ray sky is now probed down to a flux limit where the bulk of the X-ray background is almost completely resolved into discrete sources, at least in the 2–8 keV band. Extensive programs of multiwavelength follow-up observations showed that the large majority of hard X–ray selected sources are identified with Active Galactic Nuclei (AGN) spanning a broad range of redshifts, luminosities and optical properties. A sizable fraction of relatively luminous X-ray sources hosting an active, presumably obscured, nucleus would not have been easily recognized as such on the basis of optical observations because characterized by “peculiar” optical properties. In my PhD thesis, I will focus the attention on the nature of two classes of hard X-ray selected “elusive” sources: those characterized by high X-ray-to-optical flux ratios and red optical-to-near-infrared colors, a fraction of which associated with Type 2 quasars, and the X-ray bright optically normal galaxies, also known as XBONGs. In order to characterize the properties of these classes of elusive AGN, the datasets of several deep and large-area surveys have been fully exploited. The first class of “elusive” sources is characterized by X-ray-to-optical flux ratios (X/O) significantly higher than what is generally observed from unobscured quasars and Seyfert galaxies. The properties of well defined samples of high X/O sources detected at bright X–ray fluxes suggest that X/O selection is highly efficient in sampling high–redshift obscured quasars. At the limits of deep Chandra surveys (∼10−16 erg cm−2 s−1), high X/O sources are generally characterized by extremely faint optical magnitudes, hence their spectroscopic identification is hardly feasible even with the largest telescopes. In this framework, a detailed investigation of their X-ray properties may provide useful information on the nature of this important component of the X-ray source population. The X-ray data of the deepest X-ray observations ever performed, the Chandra deep fields, allows us to characterize the average X-ray properties of the high X/O population. The results of spectral analysis clearly indicate that the high X/O sources represent the most obscured component of the X–ray background. Their spectra are harder (G ∼ 1) than any other class of sources in the deep fields and also of the XRB spectrum (G ≈ 1.4). In order to better understand the AGN physics and evolution, a much better knowledge of the redshift, luminosity and spectral energy distributions (SEDs) of elusive AGN is of paramount importance. The recent COSMOS survey provides the necessary multiwavelength database to characterize the SEDs of a statistically robust sample of obscured sources. The combination of high X/O and red-colors offers a powerful tool to select obscured luminous objects at high redshift. A large sample of X-ray emitting extremely red objects (R−K >5) has been collected and their optical-infrared properties have been studied. In particular, using an appropriate SED fitting procedure, the nuclear and the host galaxy components have been deconvolved over a large range of wavelengths and ptical nuclear extinctions, black hole masses and Eddington ratios have been estimated. It is important to remark that the combination of hard X-ray selection and extreme red colors is highly efficient in picking up highly obscured, luminous sources at high redshift. Although the XBONGs do not present a new source population, the interest on the nature of these sources has gained a renewed attention after the discovery of several examples from recent Chandra and XMM–Newton surveys. Even though several possibilities were proposed in recent literature to explain why a relatively luminous (LX = 1042 − 1043erg s−1) hard X-ray source does not leave any significant signature of its presence in terms of optical emission lines, the very nature of XBONGs is still subject of debate. Good-quality photometric near-infrared data (ISAAC/VLT) of 4 low-redshift XBONGs from the HELLAS2XMMsurvey have been used to search for the presence of the putative nucleus, applying the surface-brightness decomposition technique. In two out of the four sources, the presence of a nuclear weak component hosted by a bright galaxy has been revealed. The results indicate that moderate amounts of gas and dust, covering a large solid angle (possibly 4p) at the nuclear source, may explain the lack of optical emission lines. A weak nucleus not able to produce suffcient UV photons may provide an alternative or additional explanation. On the basis of an admittedly small sample, we conclude that XBONGs constitute a mixed bag rather than a new source population. When the presence of a nucleus is revealed, it turns out to be mildly absorbed and hosted by a bright galaxy.

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In the last decade, the reverse vaccinology approach shifted the paradigm of vaccine discovery from conventional culture-based methods to high-throughput genome-based approaches for the development of recombinant protein-based vaccines against pathogenic bacteria. Besides reaching its main goal of identifying new vaccine candidates, this new procedure produced also a huge amount of molecular knowledge related to them. In the present work, we explored this knowledge in a species-independent way and we performed a systematic in silico molecular analysis of more than 100 protective antigens, looking at their sequence similarity, domain composition and protein architecture in order to identify possible common molecular features. This meta-analysis revealed that, beside a low sequence similarity, most of the known bacterial protective antigens shared structural/functional Pfam domains as well as specific protein architectures. Based on this, we formulated the hypothesis that the occurrence of these molecular signatures can be predictive of possible protective properties of other proteins in different bacterial species. We tested this hypothesis in Streptococcus agalactiae and identified four new protective antigens. Moreover, in order to provide a second proof of the concept for our approach, we used Staphyloccus aureus as a second pathogen and identified five new protective antigens. This new knowledge-driven selection process, named MetaVaccinology, represents the first in silico vaccine discovery tool based on conserved and predictive molecular and structural features of bacterial protective antigens and not dependent upon the prediction of their sub-cellular localization.

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This thesis aims at investigating methods and software architectures for discovering what are the typical and frequently occurring structures used for organizing knowledge in the Web. We identify these structures as Knowledge Patterns (KPs). KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Then we present K~ore, a software architecture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.

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In this thesis, the author presents a query language for an RDF (Resource Description Framework) database and discusses its applications in the context of the HELM project (the Hypertextual Electronic Library of Mathematics). This language aims at meeting the main requirements coming from the RDF community. in particular it includes: a human readable textual syntax and a machine-processable XML (Extensible Markup Language) syntax both for queries and for query results, a rigorously exposed formal semantics, a graph-oriented RDF data access model capable of exploring an entire RDF graph (including both RDF Models and RDF Schemata), a full set of Boolean operators to compose the query constraints, fully customizable and highly structured query results having a 4-dimensional geometry, some constructions taken from ordinary programming languages that simplify the formulation of complex queries. The HELM project aims at integrating the modern tools for the automation of formal reasoning with the most recent electronic publishing technologies, in order create and maintain a hypertextual, distributed virtual library of formal mathematical knowledge. In the spirit of the Semantic Web, the documents of this library include RDF metadata describing their structure and content in a machine-understandable form. Using the author's query engine, HELM exploits this information to implement some functionalities allowing the interactive and automatic retrieval of documents on the basis of content-aware requests that take into account the mathematical nature of these documents.

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Die Molekularbiologie von Menschen ist ein hochkomplexes und vielfältiges Themengebiet, in dem in vielen Bereichen geforscht wird. Der Fokus liegt hier insbesondere auf den Bereichen der Genomik, Proteomik, Transkriptomik und Metabolomik, und Jahre der Forschung haben große Mengen an wertvollen Daten zusammengetragen. Diese Ansammlung wächst stetig und auch für die Zukunft ist keine Stagnation absehbar. Mittlerweile aber hat diese permanente Informationsflut wertvolles Wissen in unüberschaubaren, digitalen Datenbergen begraben und das Sammeln von forschungsspezifischen und zuverlässigen Informationen zu einer großen Herausforderung werden lassen. Die in dieser Dissertation präsentierte Arbeit hat ein umfassendes Kompendium von humanen Geweben für biomedizinische Analysen generiert. Es trägt den Namen medicalgenomics.org und hat diverse biomedizinische Probleme auf der Suche nach spezifischem Wissen in zahlreichen Datenbanken gelöst. Das Kompendium ist das erste seiner Art und sein gewonnenes Wissen wird Wissenschaftlern helfen, einen besseren systematischen Überblick über spezifische Gene oder funktionaler Profile, mit Sicht auf Regulation sowie pathologische und physiologische Bedingungen, zu bekommen. Darüber hinaus ermöglichen verschiedene Abfragemethoden eine effiziente Analyse von signalgebenden Ereignissen, metabolischen Stoffwechselwegen sowie das Studieren der Gene auf der Expressionsebene. Die gesamte Vielfalt dieser Abfrageoptionen ermöglicht den Wissenschaftlern hoch spezialisierte, genetische Straßenkarten zu erstellen, mit deren Hilfe zukünftige Experimente genauer geplant werden können. Infolgedessen können wertvolle Ressourcen und Zeit eingespart werden, bei steigenden Erfolgsaussichten. Des Weiteren kann das umfassende Wissen des Kompendiums genutzt werden, um biomedizinische Hypothesen zu generieren und zu überprüfen.

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A variety of conformationally constrained aspartate and glutamate analogues inhibit the glutamate transporter 1 (GLT-1, also known as EAAT2). To expand the search for such analogues, a virtual library of aliphatic aspartate and glutamate analogues was generated starting from the chemical universe database GDB-11, which contains 26.4 million possible molecules up to 11 atoms of C, N, O, F, resulting in 101026 aspartate analogues and 151285 glutamate analogues. Virtual screening was realized by high-throughput docking to the glutamate binding site of the glutamate transporter homologue from Pyrococcus horikoshii (PDB code: 1XFH ) using Autodock. Norbornane-type aspartate analogues were selected from the top-scoring virtual hits and synthesized. Testing and optimization led to the identification of (1R*,2R*,3S*,4R*,6R*)-2-amino-6-phenethyl-bicyclo[2.2.1]heptane-2,3-dicarboxylic acid as a new inhibitor of GLT-1 with IC(50) = 1.4 ?M against GLT-1 and no inhibition of the related transporter EAAC1. The systematic diversification of known ligands by enumeration with help of GDB followed by virtual screening, synthesis, and testing as exemplified here provides a general strategy for drug discovery.

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Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

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N,N'-((4-(Dimethylamino)phenyl)methylene)bis(2-phenylacetamide) was discovered by using 3D pharmacophore database searches and was biologically confirmed as a new class of CB(2) inverse agonists. Subsequently, 52 derivatives were designed and synthesized through lead chemistry optimization by modifying the rings A-C and the core structure in further SAR studies. Five compounds were developed and also confirmed as CB(2) inverse agonists with the highest CB(2) binding affinity (CB(2)K(i) of 22-85 nM, EC(50) of 4-28 nM) and best selectivity (CB(1)/CB(2) of 235- to 909-fold). Furthermore, osteoclastogenesis bioassay indicated that PAM compounds showed great inhibition of osteoclast formation. Especially, compound 26 showed 72% inhibition activity even at the low concentration of 0.1 μM. The cytotoxicity assay suggested that the inhibition of PAM compounds on osteoclastogenesis did not result from its cytotoxicity. Therefore, these PAM derivatives could be used as potential leads for the development of a new type of antiosteoporosis agent.

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The global World Overview of Conservation Approaches and Technologies (WOCAT) initiative has developed standardised tools and methods to compile and evaluate knowledge available about SLM. This knowledge is now combined and enriched with audiovisual information in order to give a voice to land users, reach a broad range of stakeholders, and assist in scaling up SLM to reverse trends of degradation, desertification, and drought. Five video products, adapted to the needs of different target groups, are created and embedded in already existing platforms for knowledge sharing of SLM such as the WOCAT database and Google Earth application. A pilot project was carried out in Kenya and Tajikistan to verify ideas and tools while at the same time assessing the usefulness of the suggested products on the ground. Video has the potential to bridge the gap between different actor groups and enable communication and sharing on different levels and scales: locally, regionally, and globally. Furthermore, it is an innovative tool to link local and scientific knowledge, raise awareness, and support advocacy for SLM. Keywords: Sustainable Land Management (SLM), knowledge sharing, audiovisual messages, video, World Overview of Conservation Approaches and Technologies (WOCAT)

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A web service is a collection of industry standards to enable reusability of services and interoperability of heterogeneous applications. The UMLS Knowledge Source (UMLSKS) Server provides remote access to the UMLSKS and related resources. We propose a Web Services Architecture that encapsulates UMLSKS-API and makes it available in distributed and heterogeneous environments. This is the first step towards intelligent and automatic UMLS services discovery and invocation by computer systems in distributed environments such as web.