20 resultados para Search and Discovery


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To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.

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This dissertation studies the caching of queries and how to cache in an efficient way, so that retrieving previously accessed data does not need any intermediary nodes between the data-source peer and the querying peer in super-peer P2P network. A precise algorithm was devised that demonstrated how queries can be deconstructed to provide greater flexibility for reusing their constituent elements. It showed how subsequent queries can make use of more than one previous query and any part of those queries to reconstruct direct data communication with one or more source peers that have supplied data previously. In effect, a new query can search and exploit the entire cached list of queries to construct the list of the data locations it requires that might match any locations previously accessed. The new method increases the likelihood of repeat queries being able to reuse earlier queries and provides a viable way of by-passing shared data indexes in structured networks. It could also increase the efficiency of unstructured networks by reducing traffic and the propensity for network flooding. In addition, performance evaluation for predicting query routing performance by using a UML sequence diagram is introduced. This new method of performance evaluation provides designers with information about when it is most beneficial to use caching and how the peer connections can optimize its exploitation.

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3-Substituted pyrrole-2,5-diones were synthesised from mucohalogen acids and the antibacterial activity was subsequently determined in biological assays. The minimum inhibitory concentration and the minimum bactericidal concentration of 2a were determined for a wide range of microorganisms in the low micromolar range. Protein identification using SDS-PAGE and LC/MS/MS demonstrated a partly degradation of OprF-related proteins giving an insight into the underlying mechanism of these novel antibacterial agents. © 2007 Bentham Science Publishers Ltd.

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The 5-HT7 receptor is linked with various CNS disorders. Using an automated solution phase synthesis a combinatorial library of 384 N-substituted N-[1-methyl-3-(4-methylpiperidin-1-yl)propyl]-arylsulfonamides was prepared with 24 chemically diverse amines 1-24 and 16 sulfonyl chlorides A-P. The chemical library of alkylated sulfonamides was evaluated in a receptor binding assay with [3]H-5-CT as ligand. The key synthetic step was the alkylation of a sulfonamide with iodide E, which was prepared from butanediol in 4 synthetic steps. The target compounds 1A, 1B .....24A ... 24P were purified by solvent extraction on a Teacan liquid handling system. Sulfonamide J20, B23, D23, G23, G23, J23 , I24 and O24 displayed a binding affinity IC50 between 100 nM and 10 nM. The crystalline J20 (IC50=39 nM) and O24 (IC50=83 nM) were evaluated further in the despair swimming test and the tail suspension assay. A significant antidepressant activity was found in mice of a greater magnitude than imipramine and fluoxetine at low doses. © 2006 Bentham Science Publishers Ltd.

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Reading scientific articles is more time-consuming than reading news because readers need to search and read many citations. This paper proposes a citation guided method for summarizing multiple scientific papers. A phenomenon we can observe is that citation sentences in one paragraph or section usually talk about a common fact, which is usually represented as a set of noun phrases co-occurring in citation texts and it is usually discussed from different aspects. We design a multi-document summarization system based on common fact detection. One challenge is that citations may not use the same terms to refer to a common fact. We thus use term association discovering algorithm to expand terms based on a large set of scientific article abstracts. Then, citations can be clustered based on common facts. The common fact is used as a salient term set to get relevant sentences from the corresponding cited articles to form a summary. Experiments show that our method outperforms three baseline methods by ROUGE metric.©2013 Elsevier B.V. All rights reserved.