Efficient Ad-Hoc Graph Inference and Matching in Biological Databases
Summary: Formalizes ad-hoc online inference and subgraph matching of gene regulatory networks from feature databases without full materialization, via probabilistic graphs. Introduces a probabilistic edge-score and, with reduction, pruning, embedding, and index-guided query processing, to efficiently answer IM-GRN queries. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xiang Lian
- 2. Dongchul Kim
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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 |
|---|---|---|---|---|
| 6 | The R*-tree: An Efficient and Robust Access Method for Points and Rectangles | 1990 | SIGMOD | 0.0016162015 |
| 90 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB | 0.00052068982 |
| 129 | The X-tree: An Index Structure for High-Dimensional Data | 1996 | VLDB | 0.0004429571 |
| 284 | The SR-tree: An Index Structure for High-Dimensional Nearest Neighbor Queries | 1997 | SIGMOD | 0.00028994728 |
| 321 | MCDB: A Monte Carlo Approach to Managing Uncertain Data | 2008 | SIGMOD | 0.00027527389 |
| 1,162 | k-Nearest Neighbors in Uncertain Graphs | 2010 | VLDB | 0.0001358105 |
| 8,765 | Efficient Query Answering in Probabilistic RDF Graphs | 2011 | SIGMOD | 4.456315e-05 |
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