Precedence Temporal Networks to represent temporal relationships in gene expression data.

The reconstruction of gene regulatory networks from gene expression time series is nowadays an interesting research challenge. A key problem in this kind of analysis is the automated extraction of precedence and synchronization between interesting patterns assumed by genes over time. The present work introduces Precedence Temporal Networks (PTN), a novel method to extract and visualize temporal relationships between genes. PTNs are a special kind of temporal network where nodes represent temporal patterns while edges identify precedence or synchronization relationships between the nodes. The method is tested on two case studies: the expression of a subset of genes in the soil amoeba Dictyostelium discoideum and of a set of well-studied genes involved in the human cell cycle regulation. The extracted networks reflect the capability of the algorithm to clearly reconstruct the timing of the considered gene sets, highlighting different stages in Dictyostelium development and in the cell cycle, respectively.