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相关概念视频

Flow Cytometry01:23

Flow Cytometry

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The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction
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图像流细胞计:一个初始化程序.

Paul Rees1,2, Huw D Summers1, Andrew Filby3

  • 1Department of Biomedical Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, United Kingdom.

Nature reviews. Methods primers
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PubMed
概括
此摘要是机器生成的。

图像流动细胞计 (IFC) 融合了流动细胞计和显微镜,用于详细的单细胞分析. 本书探讨了IFC仪器仪表,数据和不断发展的分析方法,从门到深度学习,用于生物医学应用.

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Qualitative and Quantitative Analysis of the Immune Synapse in the Human System Using Imaging Flow Cytometry
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Author Spotlight: Advancing Research in Microbial Autoaggregation Using Imaging Flow Cytometry
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科学领域:

  • 生物医学工程 生物医学工程
  • 细胞生物学 细胞生物学
  • 数据科学数据科学数据科学

背景情况:

  • 图像流动细胞计 (IFC) 将高通量流动细胞计与显微镜的单细胞成像相结合.
  • IFC从众多图像特征生成丰富的数据集,使其能够实现多种生物医学应用.
  • 计算分析的进步对于利用IFC数据至关重要.

研究的目的:

  • 提供成像流细胞计仪器仪表,数据采集和分析的基础知识.
  • 审查IFC数据分析方法的进展情况.
  • 讨论IFC当前的局限性和未来的创新.

主要方法:

  • 讨论IFC典型的仪器仪表和数据格式.
  • 分析工具的概述,包括单个图像功能,网关,自定义功能设计和机器/深度学习.
  • 文献中的说明性示例展示了分析方法的进展和应用.

主要成果:

  • 分析方法已经从基本的网关发展到复杂的机器学习方法.
  • 不同的方法适用于各种IFC数据集和研究问题.
  • 国际金融公司已经展示了一系列新的生物医学应用.

结论:

  • IFC是一种强大的技术,用于生物医学研究中详细的单细胞分析.
  • 分析方法的发展,特别是机器学习,增强了IFC的能力.
  • 持续的创新正在解决当前的局限性,有望在未来应用更广泛.