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

Flow Cytometry01:23

Flow Cytometry

13.4K
The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
13.4K

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

Metabolomic Signatures of Relapse and Survival in AML Patients Receiving Allogeneic Hematopoietic Stem Cell Transplantation.

Hematology reports·2026
Same author

FLASH-MM: fast and scalable single-cell differential expression analysis using linear mixed-effects models.

Nature communications·2026
Same author

Tutorial: annotation of animal genomes.

Nature protocols·2026
Same author

Glioblastoma stem cells show transcriptionally correlated spatial organization.

Communications biology·2026
Same author

4R-tau seeding activity reveals molecular subtypes in progressive supranuclear palsy.

Nature communications·2025
Same author

Cholinergic synaptic plasticity shapes resilience and vulnerability to tau.

bioRxiv : the preprint server for biology·2025
Same journal

Infiltrating monocytes augment alternative complement activation and exacerbate inherited retinal degeneration in a mouse model.

Research square·2026
Same journal

Eco-evolutionary dynamics of defense systems in mobile genetic elements: Cui bono?

Research square·2026
Same journal

HIV Transmission Dynamics in Greater Mexico City are Shaped by Dense Spatial Mixing.

Research square·2026
Same journal

A UCP1-IRES-Cre Knock-In Mouse Enables Specific Brown Adipocyte Targeting Without CNS Off-Target Expression.

Research square·2026
Same journal

Precision RNAi for Fibrodysplasia Ossificans Progressiva: a combinatorial, unimolecular, allele selective approach.

Research square·2026
Same journal

Perceptions of end-of-life care quality among bereaved closest contacts of community-dwelling older Australians: a cross-sectional survey of the ASPREE cohort.

Research square·2026
查看所有相关文章

相关实验视频

Updated: May 5, 2026

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.7K

使用sciRED进行可解释的单细胞因子分解.

Delaram Pouyabahar1,2, Tallulah Andrews3,4, Gary D Bader1,2,5,6,7,8

  • 1Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

Research square
|August 16, 2024
PubMed
概括
此摘要是机器生成的。

单细胞可解释残留分解 (sciRED) 通过提高因子解释性和识别隐藏的生物信号来增强单细胞RNA测序分析. 这种方法有助于理解各种组织中复杂的基因表达数据.

更多相关视频

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations
04:32

Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations

Published on: May 31, 2020

8.0K

相关实验视频

Last Updated: May 5, 2026

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.7K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations
04:32

Fluorescence-Activated Cell Sorting for the Isolation of Scleractinian Cell Populations

Published on: May 31, 2020

8.0K

科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 揭示了细胞异质性,但面临技术噪音,稀疏性和高维度的挑战.
  • 现有的数据因子化方法需要对已识别的基因表达程序进行手动解释.
  • 改进的解释性对于从scRNA-seq数据中提取有意义的生物学见解至关重要.

研究的目的:

  • 开发一种新的方法,即单细胞可解释的残留分解 (sciRED),用于增强scRNA-seq因子分析的解释.
  • 改进复杂scRNA-seq数据集中的生物信号的识别和表征.
  • 解决混的技术因素,发现隐藏的生物现象.

主要方法:

  • sciRED采用剩余分解来消除混效应,并使用因子旋转来提高可解释性.
  • 该方法将已识别的因素映射到已知的共变量,并检测出可能代表新生物信号的无法解释的因素.
  • 基因和与产生的因素相关的生物过程被系统地确定.

主要成果:

  • 将sciRED应用于多种scRNA-seq数据集,揭示了数据中性别特异的变化.
  • 该方法在外周血液单核细胞 (PBMC) 数据中发现了不同的免疫刺激信号.
  • sciRED在老鼠肝脏数据中降低了环境RNA污染,并在人类肝脏数据中确定了罕见细胞类型特征和区分计划.

结论:

  • sciRED显著提高了scRNA-seq因子分析的解释性.
  • 该方法有效地描述了各种生物信号,包括技术变异和微妙的生物现象.
  • 在scRNA-seq研究中,sciRED为更深入的生物发现提供了有价值的工具.