TargetMine, an integrated data warehouse for candidate gene prioritisation and target discovery

Area of Science:

• Biomedical Research
• Genomics
• Bioinformatics

Background:

• Prioritizing candidate genes for experimental validation is a significant challenge in drug discovery and biomedical research.
• Integrated approaches combining diverse data types are crucial for optimal target selection.

Purpose of the Study:

• To develop TargetMine, a novel data warehouse designed for efficient and effective target prioritization.
• To enable complex data searches and integrate custom annotations and experimental data for enhanced target identification.

Main Methods:

• Utilized the InterMine framework to build TargetMine, incorporating new data models like protein-DNA interactions.
• Developed an objective protocol for target prioritization within the TargetMine system.
• Established a benchmarking procedure to rigorously evaluate the performance of the prioritization protocol.

Main Results:

• TargetMine facilitates complex data searches beyond the capabilities of existing tools.
• The developed prioritization protocol demonstrated high precision and coverage in identifying known disease-associated genes.
• Integration of custom and in-house experimental data is supported.

Conclusions:

• TargetMine provides an efficient solution for target prioritization in drug discovery and biomedical research.
• The integrated approach and novel data models enhance the identification of potential therapeutic targets.
• The demonstrated protocol offers a reliable method for selecting candidate genes for further investigation.