[人类生物年龄计算的新型整合性多omics策略.]
1Pitirim Sorokin Syktyvkar State University, 55 Oktyabrsky pr., Syktyvkar 167001, Russian Federation,
Advances in gerontology = Uspekhi gerontologii
|June 30, 2024
概括
多omics方法整合各种生物数据来计算人类的生物年龄. 虽然还没有针对个性化的抗衰老药物,但这些方法提高了对衰老过程的理解.
科学领域:
- 老年学是一门学科.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 分子年龄学越来越多地利用多omics数据来计算生物年龄.
- 之前综合方法的局限性阻碍了全面的生物年龄评估.
研究的目的:
- 为人类生物年龄计算提供多学科综合方法的概述.
- 分析整合多样化的OMIC数据集的常见方法.
主要方法:
- 对生物年龄的多omics集成现有文献的审查.
- 分析了三个主要的整合策略:连接,融合模型和转换方法 (人工智能驱动).
- 检查甲基组,转录组,蛋白质组,微生物组和代谢组数据的整合.
主要成果:
- 确定并定义了三个主要的多学科整合方法:连接,融合和转换.
- 详细介绍了使用机器学习和人工智能结合多个omics数据集的过程.
结论:
- 多学科融合为了解生物衰老提供了先进的方法.
- 在个性化抗衰老药物中直接应用目前不太可能,但对衰老机制的基本见解将得到显著的进展.
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