单细胞动态数据的计算建模
Wenbo Guo1, Zeyu Chen, Jin Gu1
1MOE Key Lab of Bioinformatics, BNRIST Bioinformatics Division, Department of Automation, Tsinghua University, No. 30 Shuangqing Road, Haidian District, Beijing 100084, China.
Briefings in bioinformatics
|June 30, 2025
概括
了解细胞动态对于生命科学和医学至关重要. 本综述涵盖了分析动态单细胞测序数据的计算挑战和算法解决方案,以探索复杂的生物过程.
科学领域:
- 计算生物学 计算生物学
- 系统生物学 系统生物学
- 基因组学就是基因组学.
背景情况:
- 单细胞测序技术可以随着时间的推移进行动态测量.
- 分析动态单细胞数据带来了重大的计算挑战.
研究的目的:
- 审查分析动态单细胞数据的挑战.
- 概述了用于表征细胞动态的算法进步.
- 讨论未来的方向,整合技术和人工智能.
主要方法:
- 阐述实验限制,数据特征和生物发现挑战.
- 对推断细胞动态,剖析机制,预测命运和整合谱系追踪的算法的概述.
- 讨论生物技术和人工智能的进展.
主要成果:
- 确定动态单细胞数据分析中的关键挑战.
- 对表征细胞动态的四个关键任务的算法解决方案的分类.
- 突出新兴技术和人工智能的潜力.
结论:
- 解决计算挑战对于推进细胞动态研究至关重要.
- 算法进步是从动态单细胞数据中解锁洞察力的关键.
- 人工智能和先进生物技术的未来整合将加强对生命过程的时空探索.
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