Darvish A, Najarian K
College of Information Technology, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Biosystems. 2006 Feb-Mar;83(2-3):125-35. doi: 10.1016/j.biosystems.2005.06.013. Epub 2005 Dec 27.
We propose a novel technique that constructs gene regulatory networks from DNA microarray data and gene-protein databases and then applies Mason rule to systematically search for the most dominant regulators of the network. The algorithm then recommends the identified dominant regulator genes as the best candidates for future knock-out experiments. Actively choosing the genes for knock-out experiments allows optimal perturbation of the pathway and therefore produces the most informative DNA microarray data for pathway identification purposes. This approach is more practically advantageous in analysis of large pathways where the time and cost of DNA microarray data experiments can be reduced using the proposed optimal experiment design. The proposed method was successfully tested on the galactose regulatory network.
我们提出了一种新技术，该技术可从DNA微阵列数据和基因-蛋白质数据库构建基因调控网络，然后应用梅森规则系统地搜索该网络中最主要的调控因子。该算法随后将识别出的主要调控因子基因推荐为未来基因敲除实验的最佳候选基因。主动选择用于基因敲除实验的基因可实现对通路的最佳扰动，从而产生用于通路识别目的的最具信息性的DNA微阵列数据。在分析大型通路时，这种方法在实际应用中更具优势，因为使用所提出的最优实验设计可以减少DNA微阵列数据实验的时间和成本。所提出的方法已在半乳糖调控网络上成功进行了测试。
