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

Classification of Skeletal Muscle Fibers01:48

Classification of Skeletal Muscle Fibers

Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...
Introduction to Fibroblasts01:09

Introduction to Fibroblasts

Rudolph Virchow discovered spindle-shaped cells called fibroblasts in 1858. Inactive fibroblasts, called fibrocytes, become activated by various stimuli, such as growth factors and inflammatory cytokines. Activated fibroblasts play a crucial role in wound healing, inflammation, formation of new blood vessels, and cancer progression. Uncontrolled activation of fibroblasts results in fibrosis, the excess deposition of fibrous tissue, which can lead to scarring and affect normal organs. This...
Subcellular Fractionation01:32

Subcellular Fractionation

The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
Differential Centrifugation
Differential centrifugation is...

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

Publisher Correction: Spatial transcriptomics uncovers vasculature-centered cellular interactions driving Japanese encephalitis progression in a mouse model.

Nature communications·2026
Same author

The potential of wheat spatial omics.

Nature genetics·2026
Same author

Spatial transcriptomics uncovers vasculature-centered cellular interactions driving Japanese encephalitis progression in a mouse model.

Nature communications·2026
Same author

Single-cell and spatial transcriptomics define 20E-driven developmental reprogramming in silkworm wing disc.

Nature communications·2026
Same author

Stereo-cell: Spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays.

Science (New York, N.Y.)·2025
Same author

CellBinDB: a large-scale multimodal annotated dataset for cell segmentation with benchmarking of universal models.

GigaScience·2025

相关实验视频

Updated: Jun 8, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

25.0K

CSRefiner:用于微调小数据集的细胞细分模型的轻量级框架.

Can Shi1,2,3, Yumei Li1,2, Jing Guo1,2

  • 1State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen, 518083, China.

Briefings in bioinformatics
|January 13, 2026
PubMed
概括

CSRefiner通过提高单细胞细分精度来增强整个组织分析的空间奥米克. 这个框架提供了一个轻量级的解决方案,用于精确的空间基因表达数据,最小的训练数据.

关键词:
细胞细分 细胞细分 细胞细分精细调整 精细调整空间的奥米克.

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

443

相关实验视频

Last Updated: Jun 8, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

25.0K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

443

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.
  • 细胞生物学 细胞生物学

背景情况:

  • 空间奥米克技术使得以亚细胞分辨率进行转录组分析.
  • 深度学习模型提供了高准确度,但与全组织分析和多样化的细胞群体作斗争.
  • 当前的微调方法往往资源密集,缺乏适应性.

研究的目的:

  • 推出CSRefiner,一种用于精确整组织单细胞空间表达分析的新型微调框架.
  • 为解决目前基于深度学习的空间转录组学的细胞细分的局限性.
  • 为实际应用提供可扩展和适应的解决方案.

主要方法:

  • 开发了CSRefiner,一个轻量级和高效的微调框架.
  • 集成支持微调空间奥米克斯中广泛使用的细分模型.
  • 在多种染色类型和多种主流模型中评估性能.

主要成果:

  • 在有限的注释数据的基础上,CSRefiner在整个组织单细胞细分方面实现了高精度.
  • 在各种染色类型中表现出卓越的性能.
  • 展示了与多个主流细分模型的兼容性.

结论:

  • CSRefiner为现实世界的空间转录学提供了一种实用且强大的解决方案.
  • 该框架将操作简单性与高精度相结合,用于精确的空间基因表达分析.
  • 从亚细胞分辨率数据中实现更可靠的生物解释.