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相关实验视频

Updated: Jul 15, 2025

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

评估基于图像的细胞分析批量校正方法.

John Arevalo¹, Ellen Su¹, Robert van Dijk¹

¹Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

bioRxiv : the preprint server for biology

|September 25, 2023

概括

此摘要是机器生成的。

批量效应阻碍了基于图像的分析数据的整合. 混合模型方法Harmony在大型细胞绘画数据集中有效地纠正了这些影响,从而实现了更好的科学发现.

科学领域:

计算生物学是一种计算生物学.
生物技术是生物技术.
基因组学就是基因组学.

关键词:

批量纠正批量纠正细胞油漆细胞油漆和的和和的和高通量表型查的高通量表型查基于图像的个人资料.机器学习是机器学习.形态分析形态分析伪批量分析伪批量分析

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Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

相关实验视频

Last Updated: Jul 15, 2025

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

背景情况:

基于图像的高通量分析生成了大量的细胞数据,用于诸如药物发现等应用.
来自不同实验室和设备的批量效应限制了数据集成和解释.
细胞成像数据对于理解生物机制至关重要.

结论:

这项工作有助于整合和解释公开的Cell Painting数据.
改进的批次校正能够从大规模成像数据集中进行强大的科学发现.
开发的基准标准有助于推进基于图像的分析数据分析.