A stochastic approach to multi-gene expression dynamics

Details A stochastic approach to multi-gene expression dynamics A stochastic approach to multi-gene expression dynamics

2005-02-14

arxiv.org/abs/q-bio/0502015v2

Biology

Quantitative Biology

Biomolecules

17 pages, 2 figures, Latex, v2 includes minor modifications

Scientific paper

10.1016/j.physleta.2005.02.066

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.

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