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Biomine: predicting links between biological entities using network models of heterogeneous databases
1Biocomputing Platforms Ltd, Innopoli 2, Tekniikantie 14, , FI-02150 Espoo, Finland. lauri.eronen@cs.helsinki.fi
BMC Bioinformatics
|June 8, 2012
Summary
Biomine integrates biological data from multiple databases to predict gene and protein connections. This system outperforms individual databases for link prediction and disease gene prioritization.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Biological databases store vast gene and protein data.
- Integrating diverse databases aids discovery of novel biological connections.
Purpose of the Study:
- To present Biomine, a system for integrating biological databases.
- To evaluate Biomine's performance in link prediction and disease gene prioritization.
Main Methods:
- Biomine integrates data into a weighted graph model.
- Link prediction uses proximity measures on the graph.
- Disease gene prioritization identifies gene clusters.
Main Results:
- Biomine outperforms single data sources for link prediction.
- Weighted edge types optimize prediction accuracy.
- Biomine effectively prioritizes disease-associated genes.
Conclusions:
- Biomine demonstrates strong potential for link prediction.
- The system performs well in gene prioritization, even without prior disease gene information.
- Biomine is a proof-of-concept system with a public query interface.
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