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

Introduction to Fibroblasts01:09

Introduction to Fibroblasts

3.9K
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...
3.9K

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

Nonparametric change-point control charts for joint monitoring of mean and covariance with application to medical imaging data.

Statistical methods in medical research·2026
Same author

Research on polygonal microcavity 9 μm quantum cascade lasers with waveguide output from a master oscillator power amplifier.

Optics express·2026
Same author

Asymmetric Oxygen Bridges: A Unified Design Framework for Enhanced Catalysis.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Lattice Strain in Au<sub>3</sub>Cu Facilitated Hydrogen Spillover for Efficient Nitrate Electroreduction to Ammonia.

ACS nano·2026
Same author

Deciphering 6-mer Spectra Distribution Rules in Coronavirus Genomes: Application to Comparative Genomic Analysis.

International journal of molecular sciences·2026
Same author

Robust Self-Healing Omniphobic Coatings Enabled by Dynamic Networks of Polyhedral Oligomeric Silsesquioxane.

ACS applied materials & interfaces·2026

相关实验视频

Updated: May 6, 2026

A Multimodal Imaging Approach Based on Micro-CT and Fluorescence Molecular Tomography for Longitudinal Assessment of Bleomycin-Induced Lung Fibrosis in Mice
07:38

A Multimodal Imaging Approach Based on Micro-CT and Fluorescence Molecular Tomography for Longitudinal Assessment of Bleomycin-Induced Lung Fibrosis in Mice

Published on: April 13, 2018

12.2K

[FPCAM:为肺纤维化进行加权的基于字典的单细胞注释模型]

Yan Shi1, Bohan Wu1, Hongxu Huang1

  • 1School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou 014010, Inner Mongolia, China.

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
|February 27, 2026
PubMed
概括

我们开发了FPCAM,这是一种用于单细胞RNA测序 (scRNA-seq) 分析的新型自动化工具. FPCAM提高了细胞类型注释的准确性和效率,在复杂的数据集中表现优于现有的方法.

关键词:
FPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMFPCAMF塞拉特特征基因选择的基因选择单元格注释 单元格注释细胞基因关联字典单细胞RNA测序 (scRNA-seq) 是一种

更多相关视频

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:38

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

1.0K
Refined Murine Model of Idiopathic Pulmonary Fibrosis
07:51

Refined Murine Model of Idiopathic Pulmonary Fibrosis

Published on: June 17, 2025

1.2K

相关实验视频

Last Updated: May 6, 2026

A Multimodal Imaging Approach Based on Micro-CT and Fluorescence Molecular Tomography for Longitudinal Assessment of Bleomycin-Induced Lung Fibrosis in Mice
07:38

A Multimodal Imaging Approach Based on Micro-CT and Fluorescence Molecular Tomography for Longitudinal Assessment of Bleomycin-Induced Lung Fibrosis in Mice

Published on: April 13, 2018

12.2K
Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:38

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

1.0K
Refined Murine Model of Idiopathic Pulmonary Fibrosis
07:51

Refined Murine Model of Idiopathic Pulmonary Fibrosis

Published on: June 17, 2025

1.2K

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:

  • 单细胞RNA测序 (scRNA-seq) 为细胞异质性分析提供了高分辨率.
  • 目前的自动化单元类型注释工具在准确性,效率和偏差方面面临限制,原因是参考依赖和手动干预.
  • 准确的注释对于理解复杂的细胞亚群和跨平台scRNA-seq数据至关重要.

研究的目的:

  • 开发FPCAM,为scRNA-seq数据提供完全自动化和准确的细胞注释工具.
  • 克服现有的注释方法的局限性,特别是对于复杂的数据集和跨平台比较.
  • 提供灵活而精确的工具,用于在各种疾病背景下进行细胞类型识别,包括肺纤维化.

主要方法:

  • FPCAM是一个基于R Shiny的工具,利用Seurat框架进行特征基因识别.
  • 它整合了相似性矩阵计算,一个精选的肺纤维化细胞基因关联字典和一个优化的评估指标.
  • 该工具采用多源标记基因数据库,具有动态更新和加权注释算法.

主要成果:

  • FPCAM实现了85.7%的准确性,超过了SCSA (82.1%) 和SciBet (78.6%).
  • 在FPCAM中,科恩的卡帕系数为0.81,高于SCSA (0.76) 和SciBet (0.73).
  • 与单一R和SciBet相比,FPCAM显示出更高的准确性和稳定性,这些文件高度依赖预定义的注释文件.

结论:

  • 在scRNA-seq研究中,FPCAM提供了高效,灵活和精确的细胞类型识别.
  • 该工具有效地解决了复杂细胞亚群和跨平台数据集的注释方面的挑战.
  • 在肺纤维化和其他疾病中,FPCAM代表了单细胞转录组研究的重大进步.