Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Highly Accessed Software

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

Andreas Keller1*, Christina Backes1, Maher Al-Awadhi1, Andreas Gerasch2, Jan Küntzer1, Oliver Kohlbacher2, Michael Kaufmann2 and Hans-Peter Lenhof1

Author Affiliations

1 Center for Bioinformatics, Saarland University, Saarbrücken, Germany

2 Wilhelm Schickard Institute for Computer Science, Eberhard Karls University, Tübingen, Germany

For all author emails, please log on.

BMC Bioinformatics 2008, 9:552  doi:10.1186/1471-2105-9-552

Published: 22 December 2008

Abstract

Background

High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline.

Results

Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms.

Conclusion

Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.