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Data integration and visualization system for enabling conceptual biology
VTT Biotechnology, Espoo, Finland.
VTT Biotechnology, Espoo, Finland.
VTT Biotechnology, Espoo, Finland.
VTT Biotechnology, Espoo, Finland.
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2005 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 21 Suppl 1, p. i177-i185Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Oxford University Press, 2005. Vol. 21 Suppl 1, p. i177-i185
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-70893DOI: 10.1093/bioinformatics/bti1015ISI: 000230273000020PubMedID: 15961455Scopus ID: 2-s2.0-29144514388OAI: oai:DiVA.org:oru-70893DiVA, id: diva2:1345891
Conference
13th International Conference on Intelligent Systems for Molecular Biology, Detroit, MI, USA, JUN 25-29, 2005
Available from: 2019-08-26 Created: 2019-08-26 Last updated: 2019-09-05Bibliographically approved

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Oresic, Matej

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf