Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data.

Autor: Stear BJ; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Mohseni Ahooyi T; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Simmons JA; Department of Biomedical Informatics, School of Medicine, The University of Pittsburgh, Pittsburgh, PA, USA., Kollar C; Department of Biomedical Informatics, School of Medicine, The University of Pittsburgh, Pittsburgh, PA, USA., Hartman L; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Beigel K; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Lahiri A; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Vasisht S; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Callahan TJ; Department of Biomedical Informatics, Columbia University Irving Medical Campus, New York, NY, USA., Nemarich CM; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA., Silverstein JC; Department of Biomedical Informatics, School of Medicine, The University of Pittsburgh, Pittsburgh, PA, USA., Taylor DM; Department of Biomedical and Health Informatics (DBHI), The Children's Hospital of Philadelphia, Philadelphia, PA, USA. taylordm@chop.edu.; Department of Pediatrics, University of Pennsylvania Perelman Medical School, Philadelphia, PA, USA. taylordm@chop.edu.
Jazyk: angličtina
Zdroj: Scientific data [Sci Data] 2024 Dec 18; Vol. 11 (1), pp. 1338. Date of Electronic Publication: 2024 Dec 18.
DOI: 10.1038/s41597-024-04070-w
Abstrakt: Over the past decade, there has been substantial growth in both the quantity and complexity of available biomedical data. In order to more efficiently harness this extensive data and alleviate challenges associated with integration of multi-omics data, we developed Petagraph, a biomedical knowledge graph that encompasses over 32 million nodes and 118 million relationships. Petagraph leverages more than 180 ontologies and standards in the Unified Biomedical Knowledge Graph (UBKG) to embed millions of quantitative genomics data points. Petagraph provides a cohesive data environment that enables users to efficiently analyze, annotate, and discern relationships within and across complex multi-omics datasets supported by UBKG's annotation scaffold. We demonstrate how queries on Petagraph can generate meaningful results across various research contexts and use cases.
Competing Interests: Competing interests: The authors declare no competing interests.
(© 2024. The Author(s).)
Databáze: MEDLINE
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