Heterogeneous database integration in biomedicine
Computers and Biomedical Research
TAMBIS: Transparent Access to Multiple Bioinformatics Information Sources
ISMB '98 Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology
Don't Scrap It, Wrap It! A Wrapper Architecture for Legacy Data Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Utilizing Multiple Bioinformatics Information Sources: An XML Database Approach
BIBE '01 Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering
Proceedings of the 2004 ACM symposium on Applied computing
DiscoveryLink: a system for integrated access to life sciences data sources
IBM Systems Journal - Deep computing for the life sciences
Integration of biological sources: current systems and challenges ahead
ACM SIGMOD Record
Accomplishments and Challenges in Bioinformatics
IT Professional
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Biological sources integration has been addressed in several frameworks, considering both information sources incompatibilities and data representation heterogeneities. Most of these frameworks are mainly focused on coping with interoperability constraints among distributed databases that contain diverse types of biological data. In this paper, we propose an XML-based architecture that extends integration efforts from the distributed data sources domain to heterogeneous Bioinformatics tools of similar functionalities (“vertical integration”). The proposed architecture is based on the mediator/wrapper integration paradigm and a set of prescribed definitions that associates the capabilities and functional constraints of each analysis tool. The resulting XML-formatted information is further exploited by a visualization module that generates comparative views of the analysis outcome and a query mechanism that handles multiple information sources. The applicability of the proposed integration architecture and the information handling mechanisms was tested and substantiated on widely-known ab-initio gene finders that are publicly accessible through Web interfaces.