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      The Semantic Web – ISWC 2020: 19th International Semantic Web Conference, Athens, Greece, November 2–6, 2020, Proceedings, Part II 

      AI-KG: An Automatically Generated Knowledge Graph of Artificial Intelligence

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          The Stanford CoreNLP Natural Language Processing Toolkit

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            Bio2RDF: towards a mashup to build bioinformatics knowledge systems.

            Presently, there are numerous bioinformatics databases available on different websites. Although RDF was proposed as a standard format for the web, these databases are still available in various formats. With the increasing popularity of the semantic web technologies and the ever growing number of databases in bioinformatics, there is a pressing need to develop mashup systems to help the process of bioinformatics knowledge integration. Bio2RDF is such a system, built from rdfizer programs written in JSP, the Sesame open source triplestore technology and an OWL ontology. With Bio2RDF, documents from public bioinformatics databases such as Kegg, PDB, MGI, HGNC and several of NCBI's databases can now be made available in RDF format through a unique URL in the form of http://bio2rdf.org/namespace:id. The Bio2RDF project has successfully applied the semantic web technology to publicly available databases by creating a knowledge space of RDF documents linked together with normalized URIs and sharing a common ontology. Bio2RDF is based on a three-step approach to build mashups of bioinformatics data. The present article details this new approach and illustrates the building of a mashup used to explore the implication of four transcription factor genes in Parkinson's disease. The Bio2RDF repository can be queried at http://bio2rdf.org.
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              Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references

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                Book Chapter
                2020
                November 01 2020
                : 127-143
                10.1007/978-3-030-62466-8_9
                77caf67c-a9d4-4541-8dd1-24da59f4d0fc
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