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相关概念视频

Overview Of Cell Separation And Isolation01:20

Overview Of Cell Separation And Isolation

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Cell separation was first achieved in 1964 by S. H. Seal, who separated large tumor cells from the smaller blood cells using filtration. Two years later, Pohl and Hawk performed experiments on how cells respond differently to a nonuniform electric field based on the cell type. Such observations were the inception of cell separation methods, which allow isolating a single cell type from a heterogeneous sample.
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相关实验视频

Updated: Jun 4, 2025

Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations
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Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations

Published on: May 31, 2020

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用SCCAF-D进行细胞类型解卷的缓解批量效应.

Shuo Feng1,2, Liangfeng Huang1,3, Anna Vathrakokoili Pournara4

  • 1GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, China.

Nature communications
|December 31, 2024
PubMed
概括
此摘要是机器生成的。

细胞类型解方法揭示了细胞比例的变化. 本研究介绍了SCCAF-D,这是一个计算工作流程,用于处理批量效应,以便在各种组织中进行可靠的分析,包括非酒精性脂肪肝疾病.

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A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts
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Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
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相关实验视频

Last Updated: Jun 4, 2025

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Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations

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A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts
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Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
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科学领域:

  • 计算生物学是一种计算生物学.
  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 细胞类型解卷方法从批量转录组学估计细胞比例.
  • 当前的基准测试通常使用来自同一来源的模拟数据,限制了现实世界的适用性.
  • 批量效应可以显著影响解卷精度.

研究的目的:

  • 评估批量效应对细胞类型解的影响.
  • 引入SCCAF-D,一种新的计算工作流程,用于强大的解卷.
  • 为了验证SCCAF-D在各种组织类型和模拟/真实数据中的性能.

主要方法:

  • 开发SCCAF-D计算工作流程.
  • 在细胞类型解过程中对批量效应的评估.
  • 使用模拟和真实批量转录学数据进行基准测试.
  • 适用于非酒精性脂肪性肝病 (NAFLD) 数据集.

主要成果:

  • 在模拟和真实批量数据中,SCCAF-D确保了高于0.75的皮尔森相关系数.
  • 工作流程在各种组织类型中展示了可靠的性能.
  • 对NAFLD的分析显示,在疾病进展过程中,细胞比例发生了显著的变化.

结论:

  • SCCAF-D为细胞类型解卷提供了一个强大的解决方案,减轻批量效应问题.
  • 该工作流提高了生物研究中转录学数据分析的可靠性.
  • SCCAF-D提供了对NAFLD等疾病的细胞动态有价值的见解.