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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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相关实验视频

Updated: Jun 27, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

空间SPM:用于比较多个空间转录基因数据集中的基因表达模式图像的统计参数映射.

Jungyoon Ohn¹, Mi-Kyoung Seo¹, Jeongbin Park¹

¹Portrai, Inc., Seoul 03136, Republic of Korea.

Nucleic acids research

|April 27, 2024

概括

空间SPM将空间转录组 (ST) 数据重建为可比的图像矩阵. 这种方法使基因表达在各种组织样本和生物状态中的像素对像素进行比较.

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相关实验视频

Last Updated: Jun 27, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Published on: July 6, 2022

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

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Published on: May 16, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

空间转录基因 (ST) 技术揭示了组织微环境中的基因表达.
通过样本对ST数据集进行比较是具有挑战性的,原因是形状和坐标的变化.
现有的方法缺乏强大的交叉样本可比性,用于详细的空间基因表达分析.

研究的目的:

开发一种新的计算方法,SpatialSPM,用于对空间转录数据的标准化分析.
为了使基因表达模式在不同的组织样本中能够直接,像素对像素进行比较.
增强对生物学上显著的空间基因表达变异的识别.

主要方法:

将ST数据重建为多维图像矩阵.
空间注册的应用用于交叉样本数据对齐.
生成统计参数图 (例如T分数,皮尔森相关系数).

主要成果:

在脏,小鼠嗅觉球和小鼠大脑ST数据集上证明了SpatialSPM的适用性.
能够在样本中直接比较特定解剖区域的基因表达.
通过统计绘图,在特定区域促进对差异表达基因的识别.

结论:

空间SPM为分析和比较空间转录数据集提供了一个高效和强大的框架.
该方法通过准确的交叉样本比较来提高ST研究的深度和特异性.
通过详细的空间基因表达分析,SpatialSPM提供了对生物功能和条件的宝贵见解.