Show simple item record Ding, Ying Wild, David J Zhu, Qian Wang, Huijun Jiao, Dazhi Dong, Xiao Chen, Bin 2011-01-25T13:31:48Z 2011-01-25T13:31:48Z 2010-05-17
dc.identifier.citation Chen, B., Dong, X., Jiao, Dazhi, Wang, H., Zhu, Q., Ding, Y. and Wild, D. (2010). Chem2Bio2RDF: A semantic framework for linking and mining chemogenomic and systems chemical biology data. BMC Bioinformatics, 2010, 11, 255. en
dc.identifier.uri en
dc.description.abstract Background: Recently there has been an explosion of new data sources about genes, proteins, genetic variations, chemical compounds, diseases and drugs. Integration of these data sources and the identification of patterns that go across them is of critical interest. Initiatives such as Bio2RDF and LODD have tackled the problem of linking biological data and drug data respectively using RDF. Thus far, the inclusion of chemogenomic and systems chemical biology information that crosses the domains of chemistry and biology has been very limited. Results: We have created a single repository called Chem2Bio2RDF by aggregating data from multiple chemogenomics repositories that is cross-linked into Bio2RDF and LODD. We have also created a linked-path generation tool to facilitate SPARQL query generation, and have created extended SPARQL functions to address specific chemical/biological search needs. We demonstrate the utility of Chem2Bio2RDF in investigating polypharmacology, identification of potential multiple pathway inhibitors, and the association of pathways with adverse drug reactions. Conclusions: We have created a new semantic systems chemical biology resource, and have demonstrated its potential usefulness in specific examples of polypharmacology, multiple pathway inhibition and adverse drug reaction - pathway mapping. We have also demonstrated the usefulness of extending SPARQL with cheminformatics and bioinformatics functionality. en
dc.language.iso en_US en
dc.publisher BMC Bioinformatics en
dc.title Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data en
dc.type Article en

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