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Bioinformatics 2005 21(Suppl 1):i177-i185; doi:10.1093/bioinformatics/bti1015
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Data integration and visualization system for enabling conceptual biology

Peddinti V. Gopalacharyulu 1, Erno Lindfors 1, Catherine Bounsaythip 1, Teemu Kivioja 1, Laxman Yetukuri 1, Jaakko Hollmén 2 and Matej Oresic 1,*

1VTT Biotechnology PO Box 1500, Espoo, FIN-02044 VTT, Finland
2Helsinki University of Technology, Laboratory of Computer and Information Science PO Box 5400, Espoo, FIN-02015 HUT, Finland

*To whom correspondence should be addressed.

Motivation: Integration of heterogeneous data in life sciences is a growing and recognized challenge. The problem is not only to enable the study of such data within the context of a biological question but also more fundamentally, how to represent the available knowledge and make it accessible for mining.

Results: Our integration approach is based on the premise that relationships between biological entities can be represented as a complex network. The context dependency is achieved by a judicious use of distance measures on these networks. The biological entities and the distances between them are mapped for the purpose of visualization into the lower dimensional space using the Sammon's mapping. The system implementation is based on a multi-tier architecture using a native XML database and a software tool for querying and visualizing complex biological networks. The functionality of our system is demonstrated with two examples: (1) A multiple pathway retrieval, in which, given a pathway name, the system finds all the relationships related to the query by checking available metabolic pathway, transcriptional, signaling, protein–protein interaction and ontology annotation resources and (2) A protein neighborhood search, in which given a protein name, the system finds all its connected entities within a specified depth. These two examples show that our system is able to conceptually traverse different databases to produce testable hypotheses and lead towards answers to complex biological questions.

Contact: matej.oresic{at}vtt.fi


Received on January 15, 2005; accepted on March 27, 2005

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