鉴定特征基因和缺陷构成的特征基因:基于生物信息学和机器学习的综合分析
Long Xi1,2, W U Zixuan1,2, Y U Yunfeng1,2
1Department of Graduate School, Hunan University of Chinese Medicine, Changsha 410208, China.
概括
这项研究确定了传统中医药中阴阳缺陷构成的关键基因,为早期疾病检测和治疗策略提供了潜在的生物标志物.
科学领域:
- 基因组学就是基因组学.
- 传统中国医药 传统中国医药
- 生物标志物发现发现
背景情况:
- 传统中医 (TCM) 宪法,特别是阴阳缺陷,为疾病预防和管理提供了一个框架.
- 识别这些构成的客观生物标志物可以增强早期疾病检测和个性化治疗.
研究的目的:
- 利用传统中医宪法 (TCMC) 作为早期疾病检测和治疗的补充方法.
- 识别与阴阳缺陷构成相关的特征和枢纽基因.
主要方法:
- 差异基因表达 (DEGs) 分析和加权基因共表达网络分析 (WGCNA) 在基因表达全集数据集上进行.
- 机器学习方法被用来识别阴阳缺陷构成的特征和枢纽基因.
- 使用外部数据集验证了枢纽基因,并使用接收器操作特征 (ROC) 分析评估了它们的诊断性能.
主要成果:
- 分别确定了15个和14个枢纽基因,分别用于阴阳缺陷构成.
- 丰富分析揭示了每个组成部分与特定信号通路的关联.
- 包括MAPK6 (共享基因) 在内的几种基因得到了验证,并显示了阴阳缺陷的诊断价值.
结论:
- 特定的基因 (例如,C7orf60,CFL2,CYTIP,GPR183,HIAT1,KLHL15,MAPK6,缺乏的PTGS2;缺乏的FUT8,TAF1D,ZNF24,MAPK6,LEPROTL1) 被确定为潜在的生物标志物.
- 这些发现提供了关于阴阳缺陷构成的病变发生的见解.
- 鉴定的生物标志物可以指导TCM的诊断方法,并为科学研究提供信息.
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