利用蛋白质-蛋白质相互作用网络预测埃博拉病毒感染相关人类基因
Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network.
作者信息
Cao HuanHuan, Zhang YuHang, Zhao Jia, Zhu Liucun, Wang Yi, Li JiaRui, Feng Yuan-Ming, Zhang Ning
机构信息
Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China.
Biomedical Research Center, CODBIO Company Ltd., Tianjin. China.
出版信息
Comb Chem High Throughput Screen. 2017;20(7):638-646. doi: 10.2174/1386207320666170310114816.
BACKGROUND
Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous.
OBJECTIVE
According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm.
CONCLUSION
We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes.
背景
埃博拉出血热（EHF）由埃博拉病毒（EBOV）引起。据报道，人类可被EBOV感染，且病死率很高。然而，EBOV与宿主之间的关联因素仍不明确。
目的
根据“关联有罪”（GBA）原则，相互作用的蛋白质很可能具有相似或相同的功能。基于这一假设，我们试图在蛋白质-蛋白质相互作用网络中使用迪杰斯特拉算法获得与EBOV感染相关的人类基因。
结论
我们希望这有助于发现新的有效治疗方法。最终，15个基因被选为潜在的与EBOV感染相关的人类基因。
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