Bioinformatics Advance Access originally published online on March 13, 2006
Bioinformatics 2006 22(11):1383-1390; doi:10.1093/bioinformatics/btl081
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Graph-based analysis and visualization of experimental results with ONDEX
1 Division of Biomathematics and Bioinformatics, Rothamsted Research AL5 2JQ Harpenden, UK
2 Faculty of Technology, Bielefeld University Germany
3 University of Koblenz Germany
*To whom correspodence should be addressed.
Motivation: Assembling the relevant information needed to interpret the output from high-throughput, genome scale, experiments such as gene expression microarrays is challenging. Analysis reveals genes that show statistically significant changes in expression levels, but more information is needed to determine their biological relevance. The challenge is to bring these genes together with biological information distributed across hundreds of databases or buried in the scientific literature (millions of articles). Software tools are needed to automate this task which at present is labor-intensive and requires considerable informatics and biological expertise.
Results: This article describes ONDEX and how it can be applied to the task of interpreting gene expression results. ONDEX is a database system that combines the features of semantic database integration and text mining with methods for graph-based analysis. An overview of the ONDEX system is presented, concentrating on recently developed features for graph-based analysis and visualization. A case study is used to show how ONDEX can help to identify causal relationships between stress response genes and metabolic pathways from gene expression data. ONDEX also discovered functional annotations for most of the genes that emerged as significant in the microarray experiment, but were previously of unknown function.
Availability: ONDEX is freely available under the GPL License and can be downloaded from SourceForge http://ondex.sourceforge.net/
Contact: Jacob.Koehler{at}bbsrc.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
Received on January 4, 2006; revised on February 16, 2006; accepted on March 2, 2006
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