CRMIPred:通过考虑它们的交叉参与的表观遗传特征来确定 cis 调节模块之间的空间相互作用
Yu-Huai Yu1, Wei-Cheng Dai1, Zhi-Hao Jiang1
1Department of Biomedical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
Computer methods and programs in biomedicine
|March 15, 2026
概括
一个新的深度学习工具CRMIPred准确地预测了Cis调节模块 (CRM) 的相互作用,进步了我们对基因调节的理解. 这种计算方法提供了一种具有成本效益和高分辨率的方法,用于识别关键的DNA元素通信.
科学领域:
- 基因组学和分子生物学
- 计算生物学和生物信息学
- 表观遗传学和转录法规范
背景情况:
- 晶体调节模块 (Cis-regulatory modules,简称CRM) 是控制甲基动物基因表达的关键DNA元素.
- CRMs可以相互作用,以合作调节目标基因,增加复杂性转录控制.
- 识别这些CRM-CRM相互作用对于理解基因调节机制至关重要.
研究的目的:
- 开发一个用于预测 cis-regulatory module (CRM) 相互作用的计算工具.
- 克服现有方法的局限性,例如低分辨率和数据污染.
- 为实验技术 (如Hi-C) 提供一个具有成本效益的替代方案,用于预先选CRM交互.
主要方法:
- 开发了CRMIPred,这是一个深度学习框架,使用基于染色体的,无数据探的分区方案.
- 采用交叉关注架构来模拟CRM之间的表观遗传交叉通话.
- 利用多轨道表观遗传特征作为交互预测的输入.
主要成果:
- 在持有测试组中,CRMIPred在持有测试组中实现了高性能,auROC为87.7%,auPRC为89.3%.
- 优于现有的工具和基准方法的表现显著 (auROC超过10.3%,auPRC超过7.2%).
- 性能增长归因于生物学上的交叉注意力机制,证明了它的稳定性.
结论:
- CRMIPred作为一种有效的预选工具,用于识别潜在的CRM交互.
- 为研究表观遗传代码和色素相互作用之间的联系提供了一个计算框架.
- 提供了关于表观遗传交叉通话如何调解CRM之间的通信的见解.
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