Titlebook: Data Integration in the Life Sciences; 10th International C Helena Galhardas,Erhard Rahm Conference proceedings 2014 Springer International

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书目名称Data Integration in the Life Sciences影响因子(影响力)




书目名称Data Integration in the Life Sciences影响因子(影响力)学科排名




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书目名称Data Integration in the Life Sciences网络公开度学科排名




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书目名称Data Integration in the Life Sciences被引频次学科排名




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书目名称Data Integration in the Life Sciences读者反馈学科排名

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Discovering Relations between Indirectly Connected Biomedical Conceptswo frequent relations, namely ., and .. Our results suggest that relation discovery using indirect knowledge is possible, with an . that can reach up to 0.8. Finally, analysis of the results indicates that the models can successfully learn expressive path patterns for the examined relations.

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ConQuR-Bio: Consensus Ranking with Query Reformulation for Biological Datatrategy. The originality of our approach thus lies in using . techniques within the context of .. The ConQuR-Bio system is able to query the EntrezGene NCBI database. Our experiments demonstrate the benefit of using ConQuR-Bio compared to what is currently provided to users. ConQuR-Bio is available to the bioinformatics community at ..

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Conference proceedings 2014issions. The papers cover a range of important topics such as data integration platforms and applications; biodiversity data management; ontologies and visualization; linked data and query processing..

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0302-9743 om 20 submissions. The papers cover a range of important topics such as data integration platforms and applications; biodiversity data management; ontologies and visualization; linked data and query processing..978-3-319-08589-0978-3-319-08590-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

CRAFT

Microservices Architecture and Designt were learned within the last decade of productive research, data generation and software development from the perspective of a modern plant research institute and present the results of a strategic realignment of the data management infrastructure. Finally, we summarise the challenges which were solved and the questions which are still open.

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https://doi.org/10.1007/978-3-319-55483-9ove its further development or apply the knowledge in their applications. Here we present REX (Region Evolution Explorer) a web-based system for exploring the evolution of ontology parts (regions). REX provides an interactive and user-friendly interface to identify (un)stable regions in large life science ontologies and is available at ..

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