基因组数据分析中的生物信息学和人工智能:当前的进展和未来的方向
David B Olawade1,2,3, Ayomikun Kade4, Eghosasere Egbon5
1Department of Allied and Public Health, School of Health, Sport and Bioscience, University of East London, London, UK. d.olawade@yorksj.ac.uk.
Molecular genetics and genomics : MGG
|December 5, 2025
概括
人工智能 (AI) 正在彻底改变基因组数据分析,提高变异调用和疾病预测等任务的准确性. 对AI来说,解决可解释性和伦理方面的挑战是关键.
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.
- 人工智能的人工智能
背景情况:
- 下一代测序数据的指数增长需要先进的计算工具.
- 传统的生物信息学方法在处理复杂,多维的基因组信息方面存在局限性.
研究的目的:
- 审查人工智能 (AI) 对基因组数据分析的影响.
- 综合当前的人工智能应用,并评估基因组学新兴技术.
主要方法:
- 在PubMed,Scopus和谷歌学者 (2010-2024) 的综合文献搜索.
- 在基因组分析管道中对人工智能应用的分析,包括变异调用,多omics集成和个性化医学.
主要成果:
- 人工智能,特别是深度学习,显著提高了变体调用,基因表达分析和疾病风险预测的准确性.
- 可解释的人工智能通过解决"黑子"问题来增强临床采用;联合学习使得保护隐私的研究成为可能.
结论:
- 人工智能是基因组研究中的变革力量,但临床翻译需要解决数据标准化,可解释性和道德问题.
- 跨学科的合作和强大的验证对于负责任的AI在基因组学中的实施至关重要.
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