ArticleGigaScience2022
Hetnet connectivity search provides rapid insights into how biomedical entities are related.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Causality and potential drug targets for hyperandrogenism and anovulation-related infertility: two-sample Mendelian randomization and colocalization analyses.Journal of ovarian research · 2025Pooled it
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- Can AI reveal the next generation of high-impact bone genomics targets?Bone reports · 2025Review
- The probability of edge existence due to node degree: a baseline for network-based predictions.GigaScience · 2024Article
- The probability of edge existence due to node degree: a baseline for network-based predictions.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
12 authors at 7 institutions in 1 country.
Funding
Abstract
backgroundHetnets, short for "heterogeneous networks," contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet, connects 11 types of nodes-including genes, diseases, drugs, pathways, and anatomical structures-with over 2 million edges of 24 types. Previous work has demonstrated that supervised machine learning methods applied to such networks can identify drug repurposing opportunities. However, a training set of known relationships does not exist for many types of node pairs, even when it would be useful to examine how nodes of those types are meaningfully connected. For example, users may be curious about not only how metformin is related to breast cancer but also how a given gene might be involved in insomnia.
findingsWe developed a new procedure, termed hetnet connectivity search, that proposes important paths between any 2 nodes without requiring a supervised gold standard. The algorithm behind connectivity search identifies types of paths that occur more frequently than would be expected by chance (based on node degree alone). Several optimizations were required to precompute significant instances of node connectivity at the scale of large knowledge graphs.
conclusionWe implemented the method on Hetionet and provide an online interface at https://het.io/search. We provide an open-source implementation of these methods in our new Python package named hetmatpy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.