一个可扩展的计算框架,用于从候选cis-regulatory元素中预测基因表达
Qinhu Zhang1,2, Siguo Wang1, Zhipeng Li1
1Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo 315201, China.
Genome research
|January 16, 2026
概括
我们开发了ScPGE,这是一个计算框架,用于从cis调节元素预测基因表达. ScPGE提高了识别增强剂-基因相互作用的准确性,并揭示了调节模式,增强了我们对基因调节的理解.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 分子生物学分子生物学
背景情况:
- 了解基因表达中的cis-regulatory element (CRE) 功能至关重要,但由于动态的CREs而具有挑战性.
- 从CREs中预测基因表达仍然是分子生物学中一个重大未解决的问题.
研究的目的:
- 开发一个可扩展的计算框架 (ScPGE) 来预测候选CREs (cCREs) 的基因表达.
- 提高识别活性增强剂-基因相互作用的准确性和理解监管机制.
主要方法:
- ScPGE将DNA序列,转录因子 (TF) 结合得分和cCREs的表观基因组数据集成到3D张量器中.
- 它采用混合模型,结合卷积神经网络和变压器来分析cCRE基因关系.
- 注意力机制被用来识别关键的增强剂-基因相互作用.
主要成果:
- 在基因表达预测和增强剂-基因相互作用识别方面,ScPGE的表现优于现有的最先进模型.
- 分析显示,cCREs的调节作用随着距离目标基因的距离而减少.
- 结合染色素循环增强了SCPGE捕获远程cCRE基因相互作用的能力.
- ScPGE确定了关键的TF动机,并阐明了cCREs的不同监管作用.
结论:
- ScPGE提供了一个强大的和可扩展的框架来破译CRE基因的监管关系.
- 该模型对距离依赖效应和染色素循环的实用性的发现为基因调节提供了新的见解.
- ScPGE有助于发现监管元素并了解它们的功能机制.
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