Li Haixia, Guo Qian
Department of Neurology, The 2nd People's Hospital of Liaocheng, 306 Jiankang Road, Linqing, Liaocheng, 252600, Shandong Province, People's Republic of China.
Biotechnol Lett. 2017 Dec;39(12):1835-1842. doi: 10.1007/s10529-017-2430-2. Epub 2017 Sep 5.
To explore potential biomarkers in stroke based on ego-networks and pathways.
EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke.
Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.
基于自我网络和通路探索中风潜在的生物标志物。
应用自我网络方法，利用E-GEOD-58294转录谱和蛋白质-蛋白质相互作用（PPI）数据，在中风中寻找潜在的生物标志物。根据前5%排名的z分数和度数>1的标准，从PPI网络中鉴定出8个自我基因。选择了8个分类准确率≥0.9的候选自我网络。进行随机化检验后，鉴定出7个调整后p值<0.05的显著自我网络。然后用这些自我网络进行通路富集分析，以寻找显著通路。最后，鉴定出两条显著通路，7个自我网络中有6个富集到“3'-UTR介导的翻译调控”通路，表明该通路在中风发展中起重要作用。
利用自我网络构建了7个自我网络，并鉴定出两条显著富集的通路。这些可能为中风发展的潜在生物标志物提供新的见解。
