生物网络的联合嵌入,以实现跨物种的功能对齐
Lechuan Li1, Ruth Dannenfelser1, Yu Zhu2
1Department of Computer Science, Rice University, Houston, TX 77005, United States.
Bioinformatics (Oxford, England)
|August 26, 2023
概括
这项研究介绍了嵌入到网络对齐 (ETNA) 的方法,这是一种用于跨物种疾病基因发现的新方法. ETNA对基因网络进行调整,以提高对功能关系的理解,并确定潜在的药物重定向机会.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 系统生物学 系统生物学
背景情况:
- 模型生物对于理解人类疾病机制至关重要.
- 单独的序列相似性不足以实现物种间的功能转移.
- 蛋白质与蛋白质相互作用越来越多地被用来弥合物种特异性发现.
研究的目的:
- 开发一种用于跨物种网络对齐的新型计算方法.
- 改善模型生物和人类之间功能信息的传输.
- 确定潜在的治疗点,并促进药物的重新用途.
主要方法:
- 网络调整 (ETNA) 的拟议嵌入,一个共同的嵌入方法.
- 基于拓结构生成的个别网络嵌入.
- 采用一种以自然语言处理为灵感的交叉训练方法,用于使用基于序列的正义词进行对齐.
主要成果:
- ETNA保留了物种内部和物种间的基因功能关系.
- 该方法有效地捕捉了对和组的功能相关性.
- ETNA的嵌入使遗传相互作用的转移和表型对齐的识别成为可能.
结论:
- ETNA为跨物种功能基因组学提供了一个强大的新工具.
- 该方法支持翻译研究和药物重用倡议.
- ETNA提高了模型生物在人类疾病研究中的实用性.
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