Linking life sciences data using graph-based mapping

B - Book chapters etc edited externally

Taubert, J., Hindle, M. M., Lysenko, A., Weile, J., Kohler, J. and Rawlings, C. J. 2009. Linking life sciences data using graph-based mapping. in: Paton, N. W., Hedeler, C. and Missier, P. (ed.) Data Integration in the Life Sciences. DILS 2009. Lecture Notes in Computer Science Volume 564 Springer, Berlin. pp. 16-30

AuthorsTaubert, J., Hindle, M. M., Lysenko, A., Weile, J., Kohler, J. and Rawlings, C. J.
EditorsPaton, N. W., Hedeler, C. and Missier, P.
Abstract

There are over 1100 different databases available containing primary and derived data of interest to research biologists. It is inevitable that many of these databases contain overlapping, related or conflicting information. Data integration methods are being developed to address these issues by providing a consolidated view over multiple databases. However, a key challenge for data integration is the identification of links between closely related entries in different life sciences databases when there is no direct information that provides a reliable cross-reference. Here we describe and evaluate three data integration methods to address this challenge in the context of a graph-based data integration framework (the ONDEX system). A key result presented in this paper is a quantitative evaluation of their performance in two different situations: the integration and analysis of different metabolic pathways resources and the mapping of equivalent elements between the Gene Ontology and a nomenclature describing enzyme function.

KeywordsGene Ontology; Data Integration; Enzyme Commis; Graph Neighbourhood; Enzyme Class
Page range16-30
Year of Publication2009
Book titleData Integration in the Life Sciences. DILS 2009. Lecture Notes in Computer Science Volume 564
PublisherSpringer, Berlin
SeriesLecture Notes in Computer Science
ISBN978-3-642-02879-3
Digital Object Identifier (DOI)doi:10.1007/978-3-642-02879-3_3
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
From data to knowledge / the ONDEX System for integrating Life Sciences data sources
Integration of 'omics databases and novel approaches to data analysis and annotation
A systems approach to candidate gene and pathway identification
Project: 4918
Open accessPublished as non-open access
Output statusPublished
Copyright licensePublisher copyright

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