采用协同生物信息学和机器学习框架来阐明将喘与pyrimidine代谢基因相关联的生物标志物
Dihui Zhang1, Xiaowei Pu2, Man Zheng3
1Orthopedics department The Second Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, 510000, China.
Respiratory research
|August 31, 2024
概括
这项研究确定了11个与喘有关的pyrimidine代谢基因 (PyMGs),为诊断和监测提供了潜在的生物标志物. 这些发现提升了对喘的理解.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 代谢途径 代谢途径
背景情况:
- 喘是一种慢性炎症疾病,受遗传和环境的影响.
- 喘的分子机制尚未完全理解.
- 胺代谢 (PyM) 异常越来越多地与喘病理学有关.
研究的目的:
- 调查胺代谢基因 (PyMGs) 在喘中的作用.
- 为了确定喘潜在的诊断生物标志物.
主要方法:
- 对31个PYMG进行生物信息学分析.
- 不同基因表达分析.
- 基因组丰富分析 (GSEA) 和基因组变异分析 (GSVA).
- 拉索回归和支持矢量机器递归特征消除 (SVM-RFE) 用于枢纽基因识别和诊断准确性.
- 使用GSE76262和GSE147878.8数据集进行验证.
主要成果:
- 十一个PyMG (DHODH,UMPS,NME7,NME1,POLR2B,POLR3B,POLR1C,POLE,ENPP3,RRM2B,TK2) 与喘有显著的相关性.
- 这些基因参与RNA拼接,解剖结构维护和 purin代谢.
结论:
- 十一种PYMG是喘病原体的核心,并作为潜在的生物标志物.
- 这些发现提高了对喘分子机制的理解,有助于诊断和监测.
- 这项研究为非癌症病理提供了新的见解.
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