采用双模表示来预测DNA可曲性在自我监督的预训框架内.
Minghao Yang1, Shichen Zhang1, Zhihang Zheng1
1Bioscience and Biomedical Engineering Thrust, System Hub, Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511466, China.
Nucleic acids research
|February 20, 2024
概括
MIXBend使用序列和物理化学特性准确预测DNA曲性. 这种计算模型推进了基因组分析,揭示了对DNA循环和调控元素的见解.
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:
- 测量DNA循环速率的DNA曲性,对生物过程至关重要.
- 循环测序可以测量DNA片段的循环可循,但对于大规模的DNA来说,它耗费大量资源.
- 了解DNA曲性对于破译诸如超级增强剂之类的调节元件至关重要.
研究的目的:
- 开发一种创新的计算模型,MIXBend,用于预测DNA曲性.
- 整合核酸序列和物理化学性质,以提高预测准确度.
- 阐明DNA可曲性对人类基因组调节动机的影响.
主要方法:
- 利用DNABERT (一种预训练的语言模型) 和一个具有注意力机制的卷积神经网络.
- 开发了基于序列和物理化学的提取器,用于DNA表示.
- 采用k-mer匹配模块和自我注意力融合层进行预测.
主要成果:
- 与现有的最先进的方法相比,MIXBend表现出更高的性能.
- 在酵母DNA中确定了新的和已知的动机.
- 在人类超强增强器区域和转录因子结合部位中发现了显著的可曲性变异.
结论:
- MIXBend提供了一种强大的计算方法来预测DNA曲性.
- 该模型为DNA结构功能关系提供了宝贵的见解.
- 这些发现强调了DNA曲性在基因调节中的重要性.
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