Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Scatter Plot01:15

Scatter Plot

8.5K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
8.5K
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

347
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
347
Manipulation and Analysis01:21

Manipulation and Analysis

337
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
337

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Modeling Nonstationary Time Series Using Locally Stationary Basis Processes.

Journal of time series analysis·2026
Same author

Distinct intracellular spatiotemporal expression of Calmodulin genes underlies functional diversity of Calmodulin-dependent signalling in cardiac myocytes.

Cardiovascular research·2025
Same author

Age Restricted Location Policies: A Potential Strategy for Advancing the Tobacco Endgame.

American journal of public health·2025
Same author

Indirect Correlative Light and Electron Microscopy (iCLEM): A Novel Pipeline for Multiscale Quantification of Structure From Molecules to Organs.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada·2024
Same author

Unraveling Chamber-specific Differences in Intercalated Disc Ultrastructure and Molecular Organization and Their Impact on Cardiac Conduction.

bioRxiv : the preprint server for biology·2023
Same author

Diversity of cells and signals in the cardiovascular system.

The Journal of physiology·2023

相关实验视频

Updated: Apr 30, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K

使用最近事件 (SPACE) 的空间模式分析 - - 一个最接近邻居点的模式分析框架,用于评估数字图像的空间关系.

Andrew M Soltisz1, Peter F Craigmile2, Rengasayee Veeraraghavan1,3

  • 1Department of Biomedical Engineering, College of Engineering, 2124 Fontana Labs,140 W. 19th Ave, The Ohio State University, Columbus, OH 43210, USA.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|March 18, 2024
PubMed
概括

使用最近事件 (SPACE) 的空间模式分析为分析生物结构提供了一种新的方法. 该工具通过使用点模式分析来更准确地评估空间关系,克服了传统的定位技术的局限性.

关键词:
定位化,定位化的地方.完全的空间随机性.空的空间分配空的空间分配.光显微镜的光显微镜.图像分析图像分析最靠近的邻居分布式基于对象的分析.分点模式分析分析点模式分析.空间分析就是空间分析.空间统计的空间统计.

更多相关视频

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K
Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

6.6K

相关实验视频

Last Updated: Apr 30, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K
Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

6.6K

科学领域:

  • 生命科学 生命科学
  • 显微镜的使用方法
  • 生物图像分析 生物图像分析

背景情况:

  • 对生物结构的定量描述具有挑战性.
  • 由于信号重叠和对图像质量的敏感性,像皮尔森相关性和曼德斯共发生等传统方法存在缺陷.
  • 这些方法难以区分真实与偶然的定位.

研究的目的:

  • 引入了一个新的图像分析工具,即使用最近事件 (SPACE) 进行空间模式分析.
  • 杆点模式分析用于在显微镜图像中准确地描述空间关系.
  • 为传统的同居化方法提供了更好的替代方案.

主要方法:

  • 使用最近事件 (SPACE) 工具开发了空间模式分析.
  • 采用基于最近邻居的点模式分析.
  • 应用 SPACE 来分析心脏肌细胞图像中的mRNA和细胞核之间的空间关联.

主要成果:

  • 与传统的同居化方法相比,SPACE表现出更高的性能.
  • 评估了心脏肌细胞中mRNA和细胞核的空间关联.
  • 使用合成和实证数据评估了SPACE对图像分割,信号丰度和分辨率的灵敏度.

结论:

  • SPACE为显微镜中的定量空间分析提供了一个强大的框架.
  • 该工具克服了基于强度的局部化方法的关键限制.
  • SPACE 是显微镜师工具包中一个有价值的补充,用于准确的生物结构分析.