Graph Association Analyses for Early Drug Discovery
Summary: MedHunter builds a biomedical knowledge graph (DDKG) by integrating 11 biochemical sources with heterogeneous entity resolution, and supports incremental enrichment and cleaning. It introduces graph association rules (GARs)—graph-pattern rules that embed ML predicates—to discover drug–disease links, PPIs and DDIs and to drive extraction/cleaning. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Wenfei Fan
- 2. Daji Li
- 3. Peiyu Liang
- 4. Shuhao Liu
- 5. Yaoshu Wang
- 6. Yiming Wang
- 7. Min Xie
- 8. Runjie Zhang
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,190 | word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data | 2020 | PODS | 0.00013438056 |
| 7,287 | Discovering Association Rules from Big Graphs | 2022 | VLDB | 4.7762276e-05 |
| 8,211 | Capturing Associations in Graphs | 2020 | VLDB | 4.5581054e-05 |
| 8,422 | Deducing Certain Fixes to Graphs | 2019 | VLDB | 4.5167705e-05 |
| 9,487 | Making It Tractable to Catch Duplicates and Conflicts in Graphs | 2023 | SIGMOD | 4.3341665e-05 |
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