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Issue title: 3rd International Conference on Bioinformatics of Genome Regulation and Structure (BGRS 2002), June 2002, Novosibirsk, Russia
Article type: Research Article
Authors: Freier, Andreas | Hofestädt, Ralf | Lange, Matthias
Affiliations: Bioinformatics/Medical Informatics Department, Bielefeld University, Bielefeld, Germany | IPK Gatersleben, Corrensstraße 3, D-06466, Gatersleben, Germany
Note: [] Corresponding author: Bioinformatics/Medical Informatics Department, Bielefeld University, P.O. Box 10 01 31, D-33619 Bielefeld, Germany. E-mail: [email protected]
Abstract: The long-term objective of our work is the computational construction of complex cellular systems. Therefore, input data must be prepared systematically first. In the field of biological data information is spread out over hundreds of molecular databases. Different approaches of data integration have been already applied in the past to provide a homogeneous access to these databases. Actually, a system is required to store integrated data of different type locally and to search for networks found in the integrated dataset. Finally, the analysis of these networks can answer different questions, e.g. the role of biochemical substances in regulatory systems or the reasoning of metabolic diseases. In this article a novel object-oriented modelling approach in the field of biochemical networks is presented. Molecular objects are modelled conceptually using object classes, internally based on the object model OMG IDL. Specific object services are implemented automatically for each model and object instances are built using data integration. In combination with that, a specific view concept based on access paths has been implemented to model biochemical reaction rules automatically. Together with the application of graphical methods, pathways and cliques are computed by the system. They provide the topology of cellular process networks. The system has been implemented using Java and CORBA.
Keywords: object-oriented modelling, data integration, network analysis, Java, CORBA
Journal: In Silico Biology, vol. 3, no. 1-2, pp. 215-227, 2003
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