  In the last years, tens of thousands gene expression profiles for cells of
several organisms have been monitored. Gene expression is a complex
transcriptional process where mRNA molecules are translated into proteins,
which control most of the cell functions. In this process, the correlation
among genes is crucial to determine the specific functions of genes. Here, we
propose a novel multi-dimensional stochastic approach to deal with the gene
correlation phenomena. Interestingly, our stochastic framework suggests that
the study of the gene correlation requires only one theoretical assumption
-Markov property- and the experimental transition probability, which
characterizes the gene correlation system. Finally, a gene expression
experiment is proposed for future applications of the model.
