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Open Access Research article

Employing conservation of co-expression to improve functional inference

Carsten O Daub13* and Erik LL Sonnhammer12

Author Affiliations

1 Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden

2 Stockholm Bioinformatics Center, Albanova, Stockholm University, 10691 Stockholm, Sweden

3 Omics Science Center, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Yokohama, Kanagawa 230-0045, Japan

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BMC Systems Biology 2008, 2:81  doi:10.1186/1752-0509-2-81

Published: 22 September 2008

Abstract

Background

Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species.

Results

We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method.

Conclusion

To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results.