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pmid:37140542
Metapaths: similarity search in heterogeneous knowledge graphs via meta-paths.
Ayush Noori · Michelle M Li · Amelia L M Tan · Marinka Zitnik
Bioinformatics (Oxford, England) · 2023 doi:10.1093/bioinformatics/btad297
Paper
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Experiment
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Data
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Complete file
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Analytical methods for KGs rely on quantifying similarities between entities, such as nodes, in the graph. However, such methods must consider the diversity of node and edge types contained within the KG via, for example, defined sequences of entity types known as meta-paths. We present metapaths, the first R software package to implement meta-paths and perform meta-path-based similarity search in heterogeneous KGs. The metapaths package offers various built-in similarity metrics for node pair comparison by querying KGs represented as either edge or adjacency lists, as well as auxiliary aggregation methods to measure set-level relationships. Indeed, evaluation of these methods on an open-source biomedical KG recovered meaningful drug and disease-associated relationships, including those in Alzheimer's disease. 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