在CRISPR/Cas9基因编辑中用于预测建模的人工智能:对方法和设计策略的调查
Jay Patel1, Dhruvi Patel1, Aanal Raval1
1Department of Artificial Intelligence and Data Science, Graduate School of Engineering and Technology, Gujarat Technological University, Ahmedabad, Gujarat, India.
The journal of gene medicine
|December 10, 2025
概括
人工智能和机器学习正在增强基因组编辑技术,如CRISPR-Cas. 这些计算工具提高了预测准确性,安全性和医学和农业的治疗应用.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 克里斯普尔-卡斯系统及其变体彻底改变了基因组编辑.
- 人工智能 (AI) 和机器学习 (ML) 越来越多地融入到生物研究中.
研究的目的:
- 提供人工智能介导的基因组编辑计算发展的综合调查.
- 评估AI/ML方法,数据策略和各种生物医学领域的应用.
- 解决模型解释性,伦理学和临床翻译方面的挑战.
主要方法:
- 对基因组编辑的预测算法和深度学习框架的审查和合成.
- 对以数据为中心的策略和序列编码表示的分析.
- 评估AI/ML在瘤学,神经学,罕见病和精密医学中的应用.
主要成果:
- 人工智能/ML显著提高了基因组编辑的特异性,吞吐量和预测能力.
- 确定了需要改进的关键领域,包括数据集偏差和模型可解释性.
- 开发了人工智能介导的基因组编辑方法的分类学.
结论:
- 人工智能具有巨大的潜力,可以推进安全,有效和可访问的基因组工程.
- 需要进一步的研究来克服目前临床翻译的限制.
- 人工智能集成有望改进治疗设计并加速生物医学研究.
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