增强的流量潜力分析将酶表达的变化与代谢流量的变化联系起来
Xuhang Li1, Albertha J M Walhout2, L Safak Yilmaz3
1Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Molecular systems biology
|February 17, 2025
概括
代谢流量变化最好通过途径水平的酶表达来预测,而不仅仅是单个反应或整个网络. 一种增强的流量潜力分析 (eFPA) 算法使用这个原理进行可靠的代谢预测.
科学领域:
- 系统生物学 系统生物学
- 代谢工程是代谢工程.
- 计算生物学 计算生物学
背景情况:
- 目前的算法根据酶水平预测代谢活动,假设直接的流量相关性.
- 代谢流量也受到全调节和质量作用的影响,而不仅仅是酶表达.
- 需要对酶表达和流量关系进行系统的探索.
研究的目的:
- 研究酶表达变化与代谢流量变化之间的关系.
- 开发一种新的算法,即增强的流量潜力分析 (eFPA),用于预测代谢流量.
- 评估算法对酵母和人类数据的性能,包括单细胞应用.
主要方法:
- 结合了酵母的蛋白质和流体数据.
- 开发了增强的流量潜力分析 (eFPA) 算法,集成酶表达和网络架构.
- 应用eFPA对人类蛋白质组,转录组和单细胞基因表达数据.
主要成果:
- 流量变化最好通过途径水平的酶水平来预测,超越反应或整个网络的分析.
- eFPA准确地预测相对流量水平,即使对于非表达式调节的反应.
- eFPA 一致地预测人体组织的代谢功能,并稳定地处理稀疏,杂的单细胞数据.
结论:
- 途径级酶表达提供了比以前假设的更准确的代谢流量的预测.
- eFPA算法提供了一种强大而高效的方法,用于从表达数据中预测代谢流量.
- eFPA在不同的生物和数据类型中展示了广泛的适用性,包括单细胞分辨率.
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