基础科学和病原发生学
Emily Greenfest-Allen1, Yuk Yee Leung1, Wan-Ping Lee1
1Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 23, 2025
概括
阿尔茨海默病测序项目 (ADSP) 为AI/ML研究人员提供了用于阿尔茨海默病 (AD) 研究的大量基因组数据. 这些数据支持预测建模,生物标志物发现和精准医学治疗目标识别.
科学领域:
- 基因组学就是基因组学.
- 人工智能的人工智能
- 机器学习 机器学习
- 精准医学是一门精准的医学.
背景情况:
- 阿尔茨海默病 (AD) 研究正在探索基因组的前沿.
- 阿尔茨海默氏病测序项目 (ADSP) 为AI/ML研究人员提供了重要的机会.
- ADSP数据可以推动预测建模,生物标志物识别和治疗目标开发方面的发现.
研究的目的:
- 为AI/ML研究人员引入通过ADSP可用的基因组资源.
- 突出ADSP数据在促进阿尔茨海默病研究和精准医学方面的潜力.
- 探索使用ADSP数据集进行数据驱动发现的巨大可能性.
主要方法:
- ADSP集成了许多项目,分析了多达15万个完整的基因组和相关的临床/功能数据.
- 专注于揭开阿尔茨海默病的遗传情景,以推进精准医学.
- 利用多样化的人口数据,全面了解遗传基础.
主要成果:
- 在第5版中,ADSP强调多样性,包括来自57,302名参与者的整个基因组 (包括代表性不足的群体).
- 跨队列的表型协调促进了比较分析.
- 对总结统计,遗传关联和功能注释的开放访问使知识库生成成为可能.
- 功能性基因组学的整合,以了解超越遗传变异的生物机制.
结论:
- 在ADSP中AI/ML的潜力强调了AI/ML研究人员和阿尔茨海默氏症研究社区之间需要的合作.
- 人工智能/ML与阿尔茨海默氏症研究之间的协同作用可以带来突破.
- 来自ADSP的基因组见解可以转化为阿尔茨海默病的临床进展.
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