签名蛋白质-蛋白质相互作用网络
Lorenzo Federico Signorini1,2, Martin Kupiec2, Roded Sharan1
1Blavatnik School of Computer Science and AI, Tel Aviv University, Tel Aviv, 6997801, Israel.
Bioinformatics (Oxford, England)
|December 22, 2025
概括
我们开发了SIGNAL,这是一个新的算法,用于用激活/抑制信号对蛋白质-蛋白质相互作用网络进行注释. 这种方法使用网络传播和机器学习来预测细胞信号通路中的功能角色.
科学领域:
- 系统生物学 系统生物学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 蛋白与蛋白相互作用 (PPI) 是细胞信号通路的基础.
- 实验PPI数据缺乏功能信息,例如激活或抑制 (标志).
- 阐述相互作用标志对于构建细胞信号传递的逻辑模型至关重要.
研究的目的:
- 开发一种用于注释PPI网络与交互标志的计算方法.
- 为了能够预测信号通路内的功能角色.
主要方法:
- 开发了SIGNAL (SIGN注释算法) 方法.
- 利用路径效应的乘法模型.
- 使用网络传播来评估对基因表达的边缘影响.
- 使用基于网络特征的符号预测分类器.
主要成果:
- 信号成功地注释了PPI网络的激活/抑制标志.
- 使用现有的注释验证了方法.
- 证明了SIGNAL在预测基因表达和端粒长度上的淘汰效应方面的实用性.
结论:
- 信号为PPI网络提供了功能性注释的新方法.
- 该方法增强了对细胞信号通路的理解.
- 信号有助于预测细胞对干扰的反应.
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