多主题数据集成用于基于拓的路径激活评估和个性化药物排名
Nicolas Borisov1,2, Yaroslav Ilnytsky3,4, Boseon Byeon5
1Armenian Bioinformatics Institute, 7 Ezras Hasratyan str., 0014, Yerevan, Armenia. Nicolas.borissoff@abi.am.
Molecular omics
|October 1, 2025
概括
这项研究将包括DNA甲基化和各种RNA类型在内的多omics数据集成到一个统一的生物信息平台中. 这种新的方法增强了基因表达调节和药物效率的分析,为复杂的生物数据提供了一种标准化的方法.
科学领域:
- 生物信息学是一种生物信息学.
- 分子生物学分子生物学
- 系统生物学 系统生物学
背景情况:
- 多omics分析对于理解复杂的生物系统至关重要,但缺乏标准化的集成协议.
- 目前的方法难以统一整合多种omics数据,例如DNA甲基化和各种RNA配置文件.
研究的目的:
- 开发和验证一个统一的生物信息平台,用于整合DNA甲基化,mRNA,miRNA和lncRNA数据.
- 评估这个平台对信号通路影响分析 (SPIA) 和药物效率指数 (DEI) 计算的有用性.
- 调查不同欧米克层及其调节器之间的相关性.
主要方法:
- 整合DNA甲基化,mRNA,miRNA和lncRNA表达数据.
- 开发一个用于数据分析的联合生物信息平台.
- 信号通路影响分析 (SPIA) 和药物效率指数 (DEI) 的计算.
- 对原始和修改的DEI值与DNA甲基组数据进行比较分析.
主要成果:
- 与原来的DEI相比,镜像和平衡的DEI值与DNA甲基组数据更好地匹配.
- 蛋白质编码mRNA表达值与反意义lncRNA值的相关性比与miRNA值的相关性更强.
- 在基于mRNA和基于反意义 lncRNA的值之间观察到普遍的正相关性.
- 该平台成功实现了跨多个omics级别的基因表达调节的综合分析.
结论:
- 开发的平台提供了一个强大的方法来整合多omics数据,包括DNA甲基化和非编码RNAs.
- 这种综合性方法改善了基因表达调节的分析及其与表观遗传修饰的关系.
- 这些发现表明,反感性lncRNAs在调节蛋白质编码基因表达方面发挥着重要作用,与mRNA水平相比.
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