基于深度学习预测的健身景观的隔离式cis-regulatory元素的新设计
Haochen Wang1, Yanhui Xiang2, Ziming Liu2
1Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China.
Nucleic acids research
|July 4, 2025
概括
我们开发了一种新的绝缘设计策略,用于生物工程中的精确基因控制. 这种方法使宿主独立的转录活动预测和各种应用的de novo促进器设计成为可能.
科学领域:
- 合成生物学 合成生物学
- 分子生物学分子生物学
- 生物工程是生物工程.
背景情况:
- 精确的基因活动控制对生物工程至关重要.
- 宿主细胞环境的影响使基因调节建模复杂化.
- 现有的方法与上下文依赖的监管过程作斗争.
研究的目的:
- 为独立于宿主的转录活动引入一种绝缘设计策略.
- 建立一个可控的转录监管系统.
- 为了实现精确的建模和基因调节元件的新设计.
主要方法:
- 整合异质的 cis 和 trans 调节模块到一个直角宿主细胞中.
- 使用深度学习算法与实验数据净化.
- 开发一个主机独立的活动景观,用于主办方的设计.
主要成果:
- 成功设计了具有宿主独立活性的de novo转录促进子序列.
- 活动景观准确地捕获了转录活动.
- 为不同的RNA聚合酶生成多种不同的cis-regulatory序列.
- 实现了细菌和哺乳动物细胞中促进体活性的精确预测.
结论:
- 绝缘设计策略可以净化和建模宿主独立的转录活动.
- 功能性cis-regulatory序列的de novo设计是可以实现的.
- 这种方法在不同的细胞系中提供了精确的可预测性.
- 该策略可以扩展到其他复杂的cis-regulatory元素.
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