Confirmation of human protein interaction data by human expression data.
BACKGROUND
With microarray technology the expression of thousands of genes can be measured simultaneously. It is well known that the expression levels of genes of interacting proteins are correlated significantly more strongly in Saccharomyces cerevisiae than those of proteins that are not interacting. The objective of this work is to investigate whether this observation extends to the human genome.


RESULTS
We investigated the quantitative relationship between expression levels of genes encoding interacting proteins and genes encoding random protein pairs. Therefore we studied 1369 interacting human protein pairs and human gene expression levels of 155 arrays. We were able to establish a statistically significantly higher correlation between the expression levels of genes whose proteins interact compared to random protein pairs. Additionally we were able to provide evidence that genes encoding proteins belonging to the same GO-class show correlated expression levels.


CONCLUSIONS
This finding is concurrent with the naive hypothesis that the scales of production of interacting proteins are linked because an efficient interaction demands that involved proteins are available to some degree. The goal of further research in this field will be to understand the biological mechanisms behind this observation.
Hahn
Andreas
A
Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. andreas.hahn@mpi-sb.mpg.de
Rahnenführer
Jörg
J
Talwar
Priti
P
Lengauer
Thomas
T
D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D030562:Databases, Protein; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D015894:Genome, Human; D006801:Humans; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D011485:Protein Binding; D025941:Protein Interaction Mapping; D020543:Proteome
D020543:Proteome