Multifractal Analysis of Disease-Related Gene Networks

In this paper, we introduce a new box-covering algorithm to compute the generalized fractal dimensions of complex networks. We apply our method on networks built on disease-related gene micro array data. For each micro array data, we compare the difference of multifractal behaviour between gene networks that reconstructed from patients and normal micorarrays. The result suggests that multifractality exists in all the gene networks we generated and the differences in the shape of the D_q curves are obvious for all micro array data sets. Thus multifractal analysis could provide a potentially useful tool for gene clustering and identification between healthy people and patients.