The Use of Graph Databases in Systems Biology: A Systematic Review

How to cite: Mazein, I.; Rougny, A.; Mazein, A.; Henkel, R.; Gütebier, L.; Michaelis, L.; Ostaszewski, M.; Schneider, R.; Satagopam, V.; Jensen, L.; Waltemath, D.; Wodke, J.; Balaur, I. The Use of Graph Databases in Systems Biology: A Systematic Review. Preprints 2024, 2024031289. https://doi.org/10.20944/preprints202403.1289.v1 Mazein, I.; Rougny, A.; Mazein, A.; Henkel, R.; Gütebier, L.; Michaelis, L.; Ostaszewski, M.; Schneider, R.; Satagopam, V.; Jensen, L.; Waltemath, D.; Wodke, J.; Balaur, I. The Use of Graph Databases in Systems Biology: A Systematic Review. Preprints 2024, 2024031289. https://doi.org/10.20944/preprints202403.1289.v1

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MDPI and ACS Style

Mazein, I.; Rougny, A.; Mazein, A.; Henkel, R.; Gütebier, L.; Michaelis, L.; Ostaszewski, M.; Schneider, R.; Satagopam, V.; Jensen, L.; Waltemath, D.; Wodke, J.; Balaur, I. The Use of Graph Databases in Systems Biology: A Systematic Review. Preprints 2024, 2024031289. https://doi.org/10.20944/preprints202403.1289.v1

APA Style

Mazein, I., Rougny, A., Mazein, A., Henkel, R., Gütebier, L., Michaelis, L., Ostaszewski, M., Schneider, R., Satagopam, V., Jensen, L., Waltemath, D., Wodke, J., & Balaur, I. (2024). The Use of Graph Databases in Systems Biology: A Systematic Review. Preprints. https://doi.org/10.20944/preprints202403.1289.v1

Chicago/Turabian Style

Mazein, I., Judith Wodke and Irina Balaur. 2024 "The Use of Graph Databases in Systems Biology: A Systematic Review" Preprints. https://doi.org/10.20944/preprints202403.1289.v1

Abstract

Graph databases (GDBs) are becoming increasingly popular across scientific disciplines, being highly suitable to store and connect complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph (KG) databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available GDB technologies. Relevant publications are then categorised according to their domain and application. We detail different approaches and highlight advantages of outstanding resources, such as UniProtKB, Disease Ontology, and Reactome, which provide graph-based solutions. We discuss ongoing efforts of the systems biology community to standardise and harmonise KG creation and the maintenance of integrated resources. Outlining prospects, including the use of GDBs as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of GDBs will be key for knowledge generation in systems biology and other research fields with heterogeneous data.

Keywords

graph databases; RDF; NoSQL databases; systems biology; network biology; ontology

Subject

Computer Science and Mathematics, Mathematical and Computational Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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