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A framework for mining life sciences data on the semantic web in an interactive, graph-based environment

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

Original languageEnglish
Title of host publicationComputational Intelligence Methods for Bioinformatics and Biostatistics - 10th International Meeting, CIBB 2013, Revised Selected Papers
Number of pages13
ISBN (Electronic)978-3-319-09042-9
ISBN (Print)978-3-319-09041-2
Publication statusPublished - 16 Jul 2014
Event10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013 - Nice, France
Duration: 20 Jun 201322 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8452 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013


The last decade saw the marked increase in the availability of the Life Sciences data on the Semantic Web. At the same time, the need to interactively explore complex and extensive biological datasets lead to development of advanced visualisation tools, many of which present the data in the form of a network graph. Semantic Web technologies offer both a means to define rich semantics necessary to describe complex biological systems and allow large amounts of data to be shared effectively. However, at present the need to be familiar with relevant technologies greatly impedes access to these datasets by the non-specialist Life Sciences researches. To address this, we have developed a software frame-work that facilitates both access to the resources and presents the data returned in an intuitive, graph-based format. Our framework is closely integrated with Ondex, an established data integration solution in the Life Sciences domain. The implementation consists of two parts. The first one is a query console that allows expert users to execute Semantic Web queries directly. The second one is a graph-based interactive browsing solution that can be used to launch stock queries by choosing items in the menu. In both cases, the result is re-formatted and visualised as a graph in Ondex frontend.

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