Leo Lahti, Juha Knuuttila, Janne Nikkilä and Samuel Kaski. Exploring dependencies in the expression of orthologous man-mouse gene pairs In Bioinformatics 2004, Linköping, Sweden, June 3-6, 2004. A poster. (postscript (A4 size), gzipped postscript)

Functions of human genes are often studied indirectly, by studying model organisms such as the mouse. An underlying assumption is that so-called orthologous genes, that is, genes with a common evolutionary origin, have similar functional roles in both species. Hence it is important to study whether the orthologous genes really function in the same way. Furthermore, identifying orthologous gene groups having an unexpectedly high number of similarly expressing gene pairs may highlight important physiological similarities between the species. Diverged gene function, on the other hand, may refer to significant evolutionary changes.

Functional inter-species regularity can be sought by analyzing expression data collected from two organisms. The meaningful variation hinting at functional similarities and differences is hidden in the large and noisy data sets, and our task is to explore it.

A probabilistic associative clustering method is used for mining dependencies between the two data sets, gene expression data from orthologous mouse and human gene pairs. Associative clustering has been designed to be used in the first stage of analyzing a large data set. It presents the results as easily interpretable clusters which is a useful property for their biological interpretation.

The resulting clusters contain orthologous gene pairs with unexpected regularity between the expression profiles of the two species. Clusters with potential implications in biomedical research are chosen for a further study based on the biological interpretation of the results.

Last modified: Wed Mar 9 08:28:24 EET 2005