Methods of creating knowledge graph by linking biological databases

Nazar Zaki, Chandana Tennakoon, Hany Al Ashwal, Alanoud Al Jaberi, Amel Al Ameri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A large number of biological databases are currently in use by scientists. These databases employ different formats, many of which can be converted into resource description format (RDF), which can be subsequently queried using semantic web methods. These databases have “inter” and “intra” database relationships. RDF has an inherent graph structure that facilitates exploration of connections between data via graphical representations known as knowledge graphs. In this paper, we survey the existing methods that are in use to link biological databases and evaluate the effectiveness with which the available approaches can predict unknown links between entities in databases as a means of improving knowledge graphs.

Original languageEnglish
Title of host publicationPractical Applications of Computational Biology and Bioinformatics, 12th International Conference
EditorsMiguel Rocha, Mohd Saberi Mohamad, Juan F. De Paz, Florentino Fdez-Riverola, Pascual Gonzalez
PublisherSpringer Verlag
Pages52-62
Number of pages11
ISBN (Print)9783319987019
DOIs
Publication statusPublished - 2019
Event12th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2018 - Toledo, Spain
Duration: Jun 20 2018Jun 22 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume803
ISSN (Print)2194-5357

Other

Other12th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2018
Country/TerritorySpain
CityToledo
Period6/20/186/22/18

Keywords

  • Information retrieval
  • Knowledge graph
  • Missing links
  • Protein-protein interaction

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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