基因本体论
小桶
小RNA
机制(生物学)
计算生物学
交互网络
生物
疾病
基因
生物信息学
基因调控网络
重性抑郁障碍
基因表达
遗传学
医学
神经科学
内科学
认识论
哲学
认知
作者
Qinglai Bian,Jianbei Chen,Jiajia Wu,Fengmin Ding,Xiaojuan Li,Qingyu Ma,Liqing Zhang,Xiaojuan Zou,Jiaxu Chen
标识
DOI:10.1016/j.psychres.2021.113842
摘要
Major depressive disorder (MDD) is a highly prevalent disease and one of the main causes of disability worldwide. Although many studies have partially revealed the occurrence and development process of MDD, the pathogeny and molecular mechanisms are not fully understood. Weighted gene coexpression network analysis (WGCNA) was used to explore the co-expression modules and hub genes in MDD. A protein–protein interaction (PPI) network of the most significant module and a TF-miRNA-lncRNA regulatory network of MDD were constructed using bioinformatics analysis tools. A KEGG pathway and gene ontology (GO) functional enrichment analysis of the genes in the significant module was performed using DAVID. Five hub genes in the PPI network and 10 genes in the TF-miRNA-lncRNA regulatory network with high degree values were identified, which may provide new insights for the investigation of key pathways, diagnostic bio-markers, and therapeutic targets of MDD. This study brings a novel perspective and provides valuable information to explore the molecular mechanism of MDD.
科研通智能强力驱动
Strongly Powered by AbleSci AI