从DNA序列中预测基因变异的功能影响,基于特定环境的分子信息
Jiaxin Yang1, Sikta Das Adhikari1,2, Hao Wang1
1Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, United States.
Frontiers in systems biology
|August 14, 2025
概括
预测非编码基因变异的功能影响对于理解复杂的特征和疾病至关重要. 先进的计算模型,包括深度学习和基础模型,正在提高我们解释DNA序列遗传变异效应的能力.
科学领域:
- 遗传学 是一个遗传学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 解读非编码基因变异的功能影响是人类遗传学的一个主要挑战.
- 传统的方法,如GWAS,TWAS和QTL研究,往往掩盖了分子机制.
- 下一代测序 (NGS) 能够进行特定环境的全基因组测量,用于直接DNA序列分析.
研究的目的:
- 为预测遗传变异效应提供先进模型的系统概述.
- 探索非编码变体解释领域的挑战和未来方向.
- 提高对转录调节和疾病关联的理解.
主要方法:
- 审查传统的基于序列的模型.
- 分析深度学习模型用于变量效应预测.
- 探索最先进的基础模型.
主要成果:
- NGS技术有助于从DNA序列中直接解码遗传变异效应.
- 不同的计算模型,从传统到先进,用于变量效应预测.
- 该审查强调了预测模型的演变和能力.
结论:
- 准确预测非编码变异效应对于理解人类疾病和特征至关重要.
- 计算模型的进步,特别是深度学习和基础模型,对于进步至关重要.
- 需要继续进行研究,以应对挑战并完善预测准确性.
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