Linking life sciences data using graph-based mapping

Jan Taubert*, Matthew Hindle, Artem Lysenko, Jochen Weile, Jacob Köhler, Christopher J. Rawlings

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish
Title of host publicationData Integration in the Life Sciences - 6th International Workshop, DILS 2009, Proceedings
Number of pages15
Publication statusPublished - 2 Nov 2009
Event6th International Workshop on Data Integration in the Life Sciences, DILS 2009 - Manchester, United Kingdom
Duration: 20 Jul 200922 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5647 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Workshop on Data Integration in the Life Sciences, DILS 2009
Country/TerritoryUnited Kingdom


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