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Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database
Vadim Y Bichutskiy1, Richard Colman, Rainer K Brachmann
1Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, California 92697, USA.
Abstract:
Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.).
Insights
Integrating diverse cancer research data is crucial for finding new treatments. The Cancer Research DataBase (CRDB) demonstrates a hybrid approach to combine various data types, aiding the search for drugs targeting mutated p53 in cancer.
Area of Science:
- Biomedical Informatics
- Cancer Research
- Database Integration
Background:
- Multidisciplinary life science research necessitates integrating heterogeneous databases.
- The tumor suppressor p53 is frequently mutated in human cancers, making it a key target for cancer treatment.
- Developing small molecules to restore native function to mutated p53 is a significant goal in cancer therapy.
Purpose of the Study:
- To present the Cancer Research DataBase (CRDB) as a solution for integrating diverse cancer research data.
- To illustrate a hybrid data integration strategy combining mediation and data warehousing.
- To provide a design methodology for similar biomedical data integration systems.
Main Methods:
- Designed the Cancer Research DataBase (CRDB) to support small molecule drug discovery for cancer.
- Integrated various data types including small molecule data, computational docking results, functional assays, and protein structures.
- Employed a hybrid data integration strategy, merging mediation and data warehousing approaches.
Main Results:
- The CRDB successfully integrated heterogeneous data relevant to cancer research and drug discovery.
- The hybrid strategy proved effective for managing complex, multidisciplinary data in biomedicine.
- Demonstrated the viability of the CRDB's design for enhancing data sharing and productivity.
Conclusions:
- The hybrid data integration strategy, as exemplified by the CRDB, is a viable and effective approach for biomedical research.
- Improved data sharing through integrated databases can accelerate cancer research and increase the likelihood of successful outcomes.
- The CRDB and its design principles offer a valuable resource for the scientific community, with downloadable code and schemas.
