Bansal M, di Bernardo D
Telethon Institute of Genetics and Medicine, Via P. Castellino 111, Naples 80131, Italy.
IET Syst Biol. 2007 Sep;1(5):306-12. doi: 10.1049/iet-syb:20060079.
Genes interact with each other in complex networks that enable the processing of information and the metabolism of nutrients inside the cell. A novel inference algorithm based on linear ordinary differential equations is proposed. The algorithm can infer the local network of gene-gene interactions surrounding a gene of interest from time-series gene expression profiles. The performance of the algorithm has been tested on in silico simulated gene expression data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria Escherichia coli. This approach can infer regulatory interactions even when only a small number of measurements is available.
基因在复杂的网络中相互作用,这些网络能够处理信息并在细胞内进行营养物质的代谢。提出了一种基于线性常微分方程的新型推理算法。该算法可以从时间序列基因表达谱中推断出感兴趣基因周围的基因-基因相互作用局部网络。该算法的性能已在计算机模拟的基因表达数据以及大肠杆菌中DNA损伤反应途径(SOS途径)的九个基因子网部分上进行了测试。即使只有少量测量数据,这种方法也能推断出调控相互作用。