한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)
- 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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- Pages.11-15
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- 2003
Requirement Analysis for Bio-Information Integration Systems
- Lee, Sean (Dept. of Biosystems, Korea Advanced Institute of Science and Technology) ;
- Lee, Phil-Hyoun (Dept. of Biosystems, Korea Advanced Institute of Science and Technology) ;
- Dokyun Na (Dept. of Biosystems, Korea Advanced Institute of Science and Technology) ;
- Lee, Doheon (Dept. of Biosystems, Korea Advanced Institute of Science and Technology) ;
- Lee, Kwanghyung (Dept. of Biosystems, Korea Advanced Institute of Science and Technology) ;
- Bae, Myung-Nam (Electronics and Telecommunications Reaearch Institute)
- 발행 : 2003.09.01
초록
Amount of biological data information has been increasing exponentially. In order to cope with this bio-information explosion, it is necessary to construct a biological data information integration system. The integration system could provide useful services for bio-application developers by answering general complex queries that require accessing information from heterogeneous bio data sources, and easily accommodate a new database into the integrated systems. In this paper, we analyze architectures and mechanisms of existing integration systems with their advantages and disadvantages. Based on this analysis and user requirement studies, we propose an integration system framework that embraces advantages of the existing systems. More specifically, we propose an integration system architecture composed of a mediator and wrappers, which can offer a service interface layer for various other applications as well as independent biologists, thus playing the role of database management system for biology applications. In other words, the system can help abstract the heterogeneous information structures and formats from the application layer. In the system, the wrappers send database-specific queries and report the result to the mediator using XML. The proposed system could facilitate in silico knowledge discovery by allowing combination of numerous discrete biological information databases.
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