A comprehensive review on knowledge graphs for complex diseases. Issue 1 (18th December 2022)

• Record Type: Journal Article
• Authors: Yang, Yang; Lu, Yuwei; Yan, Wenying
• Is Part Of: Briefings in bioinformatics. Volume 24:Issue 1(2023)
• Publication Date: 2022-12-18
• Subjects: biomedicine -- complex disease -- entity extraction -- knowledge graphs -- relation extraction; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbac543
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: In recent years, knowledge graphs (KGs) have gained a great deal of popularity as a tool for storing relationships between entities and for performing higher level reasoning. KGs in biomedicine and clinical practice aim to provide an elegant solution for diagnosing and treating complex diseases more efficiently and flexibly. Here, we provide a systematic review to characterize the state-of-the-art of KGs in the area of complex disease research. We cover the following topics: (1) knowledge sources, (2) entity extraction methods, (3) relation extraction methods and (4) the application of KGs in complex diseases. As a result, we offer a complete picture of the domain. Finally, we discuss the challenges in the field by identifying gaps and opportunities for further research and propose potential research directions of KGs for complex disease diagnosis and treatment.