Form of presentation | Articles in international journals and collections |
Year of publication | 2019 |
Язык | английский |
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Tropsha Aleksandr , author
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Balkhof Dzheyms , author
Bizon Kris , author
Kebede Yafet , author
Koks Stiven , author
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Bibliographic description in the original language |
Tropsha A. ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources / Bizon C., Cox S., Balhoff J., Kebede Y., Wang P., Morton K., Fecho K., Tropsha A. // JOURNAL OF CHEMICAL INFORMATION AND MODELING. - 2019. - T. 59 (12). - p. 4968-4973. |
Annotation |
A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise when integrating data across multiple APIs due to incompatible semantic types, identifier schemes, and data formats. We present ROBOKOP KG (http://robokopkg.renci.org), which is a KG that was initially built to support the open biomedical question-answering application, ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) (http://robokop.renci.org). Additionally, we present the ROBOKOP Knowledge Graph Builder (KGB), which constructs the KG and provides an extensible framework to handle graph query over and integration of federated data sources. |
Keywords |
Pharmacology & Pharmacy; Chemistry; Computer Science |
The name of the journal |
Journal of Chemical Information and Modeling
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URL |
https://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=SourceByDais&qid=1&SID=E1yl6cKjP6VQawX9uwc&page=1&doc=1 |
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=220364&p_lang=2 |
Full metadata record ![](https://shelly.kpfu.ru/pdf/picture/arrow_black_right.gif) |
Field DC |
Value |
Language |
dc.contributor.author |
Tropsha Aleksandr |
ru_RU |
dc.contributor.author |
Balkhof Dzheyms |
ru_RU |
dc.contributor.author |
Bizon Kris |
ru_RU |
dc.contributor.author |
Kebede Yafet |
ru_RU |
dc.contributor.author |
Koks Stiven |
ru_RU |
dc.date.accessioned |
2019-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2019-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2019 |
ru_RU |
dc.identifier.citation |
Tropsha A. ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources / Bizon C., Cox S., Balhoff J., Kebede Y., Wang P., Morton K., Fecho K., Tropsha A. // JOURNAL OF CHEMICAL INFORMATION AND MODELING. - 2019. - T. 59 (12). - p. 4968-4973. |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=220364&p_lang=2 |
ru_RU |
dc.description.abstract |
Journal of Chemical Information and Modeling |
ru_RU |
dc.description.abstract |
A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise when integrating data across multiple APIs due to incompatible semantic types, identifier schemes, and data formats. We present ROBOKOP KG (http://robokopkg.renci.org), which is a KG that was initially built to support the open biomedical question-answering application, ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) (http://robokop.renci.org). Additionally, we present the ROBOKOP Knowledge Graph Builder (KGB), which constructs the KG and provides an extensible framework to handle graph query over and integration of federated data sources. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
|
ru_RU |
dc.title |
ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources |
ru_RU |
dc.type |
Articles in international journals and collections |
ru_RU |
|