建模时间和空间数据的原则和挑战.
Britta Velten1,2,3, Oliver Stegle4,5,6
1Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. britta.velten@cos.uni-heidelberg.de.
Nature methods
|September 14, 2023
概括
了解分子动力学需要时间和空间分辨率. 本综述涵盖了分析时间和空间解析的omics数据的挑战和方法,这对于生物学见解至关重要.
科学领域:
- 分子生物学分子生物学
- 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:
- 时间和空间分辨率是理解生物过程的关键.
- 高通量omics技术能够进行大规模,时间和空间分辨率的分子测量.
- 分析时空omics数据带来了独特的挑战,包括建模依赖性和跨度比较.
研究的目的:
- 提供对分析时间和空间数据的原则和挑战的概述.
- 讨论用于建模时间和空间依赖性的统计概念.
- 突出适应现有的空间时间数据分析方法的机会.
主要方法:
- 在空间时空奥米克斯数据分析中的共同原则的审查.
- 讨论用于建模时间和空间依赖性的统计概念.
- 探索方法适应时间和空间维度的数据.
主要成果:
- 识别空间时空奥米克斯数据分析中的常见挑战.
- 对建模时间和空间依赖性的统计方法的概述.
- 适应现有的分析方法的潜在策略.
结论:
- 分析时间和空间奥米克数据对于促进生物学理解至关重要.
- 时间和空间依赖的统计建模至关重要.
- 调整当前的方法可以从时空欧米克数据集中获得新的见解.
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