支持人工智能的多尺度虚拟单元:前景,挑战和机遇
Huasen Jiang1, Xiaoyu Huang1, Xiangpeng Bi1
1College of Computer Science and Technology, Ocean University of China, 238 Songling Road, Laoshan District, Qingdao 266404, China.
Briefings in bioinformatics
|March 8, 2026
概括
人工智能虚拟细胞 (AIVC) 通过模拟细胞功能提供了一个新的研究范式. 本次审查提出了AIVC的统一框架,解决了推动预测性生命科学发展的挑战.
科学领域:
- 计算生物学 计算生物学
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
背景情况:
- 传统的生物研究面临着空间时间分辨率和处理能力的局限性,以了解动态跨度生物事件.
- 人工智能 (AI) 的进步导致了AI虚拟细胞 (AIVC) 的发展,作为一种新的研究方法.
- AIVC集成了多omics数据和多学科模型,以创建模拟细胞功能和行为的数字双胞胎系统.
研究的目的:
- 为AI虚拟细胞 (AIVC) 提出统一的定义和技术框架.
- 分析"基因-蛋白质-通路-细胞"层次结构中的交叉尺度合机制.
- 提供现有的AIVC模型和数据集的全面概述.
主要方法:
- 将AIVC技术构建框架分解为跨尺度表示工程,功能子模块设计和多组件动态调节.
- 整合多主题数据和多学科模型.
- 分析生物系统中的跨尺度合机制.
主要成果:
- 为AIVC提出的统一定义和技术框架.
- 详细分析"基因-蛋白质-通路-细胞"等级交叉尺度合机制.
- 目前AIVC模型和数据集的总结,确定数据异质性和模型可解释性等关键挑战.
结论:
- AIVC代表了生命科学中的重大转变,朝着可预测性和创新迈进.
- 解决AIVC面临的挑战对于加速研究进展至关重要.
- 本综述提供了一个基本框架,以指导未来的AIVC开发和应用.
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