Graph databases in systems biology: a systematic review.

Autor:	Mazein I; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Rougny A; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg., Mazein A; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg., Henkel R; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Gütebier L; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Michaelis L; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Ostaszewski M; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg., Schneider R; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg., Satagopam V; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg., Jensen LJ; Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 15, 1870 Frederiksberg C, Denmark., Waltemath D; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Wodke JAH; Medical Informatics Laboratory, University Medicine Greifswald, Walther-Rathenau-Straße 48, Greifswald 17475, Germany., Balaur I; Luxembourg Centre for Systems Biology, University of Luxembourg, 6 Avenue du Swing, Belvaux L-4367, Luxembourg.
Jazyk:	angličtina
Zdroj:	Briefings in bioinformatics [Brief Bioinform] 2024 Sep 23; Vol. 25 (6).
DOI:	10.1093/bib/bbae561
Abstrakt:	Graph databases are becoming increasingly popular across scientific disciplines, being highly suitable for storing and connecting complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph 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 graph databases, Publications are categorized according to their domain and application, focusing on pathway and network biology and relevant ontologies and tools. We detail different approaches and highlight the 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 standardize and harmonize knowledge graph creation and the maintenance of integrated resources. Outlining prospects, including the use of graph databases as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of graph databases will be key for knowledge generation in systems biology and other research fields with heterogeneous data. (© The Author(s) 2024. Published by Oxford University Press.)
Databáze:	MEDLINE
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