Sacchi Lucia, Larizza Cristiana, Magni Paolo, Bellazzi Riccardo
Dipartimento di Informatica e Sistemistica, University of Pavia, Via Ferrata n(o) 1, 27100 Pavia, Italy.
J Biomed Inform. 2007 Dec;40(6):761-74. doi: 10.1016/j.jbi.2007.06.003. Epub 2007 Jun 10.
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.
如今，从基因表达时间序列重建基因调控网络是一项有趣的研究挑战。这类分析中的一个关键问题是自动提取基因随时间假定的有趣模式之间的先后顺序和同步性。目前的工作引入了先后顺序时间网络（PTN），这是一种提取和可视化基因间时间关系的新方法。PTN是一种特殊的时间网络，其中节点代表时间模式，而边则识别节点之间的先后顺序或同步关系。该方法在两个案例研究中进行了测试：土壤变形虫盘基网柄菌中一组基因的表达，以及一组参与人类细胞周期调控的经过充分研究的基因的表达。提取的网络反映了该算法清晰重建所考虑基因集时间安排的能力，分别突出了盘基网柄菌发育和细胞周期中的不同阶段。
