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

被引:1
作者
Stear, Benjamin J. [1 ]
Ahooyi, Taha Mohseni [1 ]
Simmons, J. Alan [2 ]
Kollar, Charles [2 ]
Hartman, Lance [1 ]
Beigel, Katherine [1 ]
Lahiri, Aditya [1 ]
Vasisht, Shubha [1 ]
Callahan, Tiffany J. [3 ]
Nemarich, Christopher M. [1 ]
Silverstein, Jonathan C. [2 ]
Taylor, Deanne M. [1 ,4 ]
机构
[1] Childrens Hosp Philadelphia, Dept Biomed & Hlth Informat DBHi, Philadelphia, PA 19104 USA
[2] Univ Pittsburgh, Sch Med, Dept Biomed Informat, Pittsburgh, PA USA
[3] Columbia Univ, Dept Biomed Informat, Irving Med Campus, New York, NY USA
[4] Univ Penn, Perelman Sch Med, Dept Pediat, Philadelphia, PA 19104 USA
关键词
GENE-EXPRESSION; SIGNATURES;
D O I
10.1038/s41597-024-04070-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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收藏
页数:28
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