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Open Access Highly Accessed Research article

Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data

Bin Chen1, Xiao Dong1, Dazhi Jiao12, Huijun Wang1, Qian Zhu1, Ying Ding2 and David J Wild1*

Author affiliations

1 School of Informatics and Computing, Indiana University, Bloomington, IN, USA

2 School of Library and Information Science, Indiana University, Bloomington, IN, USA

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Citation and License

BMC Bioinformatics 2010, 11:255  doi:10.1186/1471-2105-11-255

Published: 17 May 2010

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.