Wang Xinyan, Li Wan, Zhang Yihua, Feng Yuyan, Zhao Xilei, He Yuehan, Zhang Jun, Chen Lina
Department of Respiratory, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
PLoS One. 2017 Sep 5;12(9):e0184299. doi: 10.1371/journal.pone.0184299. eCollection 2017.
Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, in which metabolic disturbances played important roles. In this paper, functional information was integrated into a COPD-related metabolic network to assess similarity between genes. Then a gene prioritization method was applied to the COPD-related metabolic network to prioritize COPD candidate genes. The gene prioritization method was superior to ToppGene and ToppNet in both literature validation and functional enrichment analysis. Top-ranked genes prioritized from the metabolic perspective with functional information could promote the better understanding about the molecular mechanism of this disease. Top 100 genes might be potential markers for diagnostic and effective therapies.
慢性阻塞性肺疾病（COPD）是一种多因素疾病，其中代谢紊乱起着重要作用。本文将功能信息整合到COPD相关代谢网络中以评估基因间的相似性。然后将一种基因优先级排序方法应用于COPD相关代谢网络，以对COPD候选基因进行优先级排序。在文献验证和功能富集分析方面，该基因优先级排序方法均优于ToppGene和ToppNet。从代谢角度结合功能信息进行优先级排序的顶级基因有助于更好地理解该疾病的分子机制。排名前100的基因可能是诊断和有效治疗的潜在标志物。
