Abstract: The recent advent of high-throughput technology and the exponential increase in computer power have moved biology into a revolutionary mode, shifting the focus of molecular biologists from single genes to whole genomes The possibility of exploring gene function is extremely attractive in such a context of high-throughput data generation and computational inference based on similarities in gene expression has been proved to be a valuable tool for functional characterization. The modern theory of networks offers a new conceptual framework for the analysis of gene expression both at the transcriptomic and proteomic levels: genome-scale data sets can infact be conveniently visualized as networks of gene/protein co-occurrences where genes/proteins are represented by nodes and the relationships between them are represented by connections. This paper reports just an “in silico” approach to gene expression analysis based on a gene co-expression network.

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