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.
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Zaki, N., Tennakoon, C., Al Ashwal, H., Al Jaberi, A., Al Ameri, A. (2019). Methods of Creating Knowledge Graph by Linking Biological Databases. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., González, P. (eds) Practical Applications of Computational Biology and Bioinformatics, 12th International Conference. PACBB2018 2018. Advances in Intelligent Systems and Computing, vol 803. Springer, Cham. https://doi.org/10.1007/978-3-319-98702-6_7
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