Abstract
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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References
Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L., Ideker, T.: Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3), 431–432 (2011)
Goble, C., Stevens, R.: State of the nation in data integration for bioinformatics. J. Biomed. Inform. 41(5), 687–693 (2008)
Jenssen, T.K., Hovig, E.: The semantic web and biology. Drug Discov. Today 7(19), 992 (2002)
W3C: Resource Description Framework (RDF) Model and Syntax Specification, vol. 2013 (1999). http://www.w3.org/TR/PR-rdf-syntax/
W3C: SPARQL Query Language for RDF, vol. 2013 (2008). http://www.w3.org/TR/rdf-sparql-query/
Berners-Lee, T.: RFC 3986 Uniform Resource Identifier (URI): Generic Syntax, vol. 2013 (2005). http://www.rfc-editor.org/rfc/rfc3986.txt
Kohler, J., Baumbach, J., Taubert, J., Specht, M., Skusa, A., Ruegg, A., Rawlings, C., Verrier, P., Philippi, S.: Graph-based analysis and visualization of experimental results with ondex. Bioinformatics 22(11), 1383–1390 (2006)
Longabaugh, W.J.: Biotapestry: a tool to visualize the dynamic properties of gene regulatory networks. Meth. Mol. Biol. 786, 359–394 (2012)
Taubert, J., Sieren, K., Hindle, M., Hoekman, B., Winnenburg, R., Philippi, S., Rawlings, C., Khler, J.: The oxl format for the exchange of integrated datasets. J. Integr. Bioinform. 4(3), 62 (2007)
Splendiani, A., Rawlings, C.J., Kuo, S.-C., Stevens, R., Lord, P.: Lost in translation: data integration tools meet the semantic web (experiences from the ondex project). In: Gaol, F.L. (ed.) Recent Progress in DEIT, Vol. 2. LNEE, vol. 157, pp. 87–97. Springer, Heidelberg (2012)
Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Seman. Web Inf. Sys. (IJSWIS) 5(3), 1–22 (2009)
Apweiler, R., Bairoch, A., Wu, C.H., Barker, W.C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., Lopez, R., Magrane, M., Martin, M.J., Natale, D.A., O’Donovan, C., Redaschi, N., Yeh, L.S.: Uniprot: the universal protein knowledgebase. Nucleic Acids Res. 32(Database issue), D115–D119 (2004)
Goble, C.A., Bhagat, J., Aleksejevs, S., Cruickshank, D., Michaelides, D., Newman, D., Borkum, M., Bechhofer, S., Roos, M., Li, P., De Roure, D.: myExperiment: a repository and social network for the sharing of bioinformatics workflows. Nucleic Acids Res. 38(Web Server issue), W677–W682 (2010)
Belleau, F., Nolin, M.A., Tourigny, N., Rigault, P., Morissette, J.: Bio2rdf: towards a mashup to build bioinformatics knowledge systems. J Biomed. Inform. 41(5), 706–716 (2008)
Rhee, S.Y., Beavis, W., Berardini, T.Z., Chen, G., Dixon, D., Doyle, A., Garcia-Hernandez, M., Huala, E., Lander, G., Montoya, M., Miller, N., Mueller, L.A., Mundodi, S., Reiser, L., Tacklind, J., Weems, D.C., Wu, Y., Xu, I., Yoo, D., Yoon, J., Zhang, P.: The arabidopsis information resource (tair): a model organism database providing a centralized, curated gateway to arabidopsis biology, research materials and community. Nucleic Acids Res. 31(1), 224–228 (2003)
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Rothamsted Research receives grant in aid from the Biotechnology and Biological Sciences Research Council (BBSRC). This work was supported by the BBSRC award BBS/E/C/00005034.
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Lysenko, A., Grzebyta, J., Hindle, M.M., Rawlings, C.J., Splendiani, A. (2014). A Framework for Mining Life Sciences Data on the Semantic Web in an Interactive, Graph-Based Environment. In: Formenti, E., Tagliaferri, R., Wit, E. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2013. Lecture Notes in Computer Science(), vol 8452. Springer, Cham. https://doi.org/10.1007/978-3-319-09042-9_16
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