Collaborative Research: Endowing Biological Databases with Analytical Power: Indexing, Querying, and Mining of Complex Biological Structures

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The University of Southern California is awarded a grant to perform in-depth research and development of new, powerful, and scalable indexing, query processing, and data mining methods for construction of scalable, efficient, and analysis-based, heterogeneous biological database systems. The project is a joint effort between the Department of Computer Science in the University of Illinois and the Department of Molecular and Computational Biology in the University of Southern California. It will focus on a set of typical genomic and biological databases and work on the following major research themes: (1) development of efficient and scalable methods for indexing and accessing of complex biological structures, with the emphasis on mining structural patterns in large multi-graphs, mining dense recurrent graphs/networks, and similarity search on biologic structures, and (2) development of efficient and effective mechanisms for mining across heterogeneous, multi-relational bio-databases. This project will set up a solid foundation for indexing and accessing of complex biological structures and for cross-relational and cross-database analysis. Such database systems will allow access to large amounts of archival information to support biological data analysis in functional genomics, proteomics, environmental studies, and other biological and biomedical research and applications. The software systems developed in this proposal will be made freely available to the academic community. In addition, the project will develop two web databases, one on biological networks and the other on protein structures, for the biological community to efficiently retrieve and analyze the complex biological information. The new knowledge obtained from this project will be integrated into courses and textbooks on computational biology, bioinformatics, database systems, and data mining to enhance our education and training programs. The personnel working on these projects, including female and minority researchers, will be trained systematically, and new knowledge obtained will be used in education and training of information analysts, bioinformaticians, computational biologists, and university students.