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 Leukocytes01:30

Classification of Leukocytes

Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...

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

Study on acoustic emission and infrared radiation characteristics of coal combination with different tectonic coal thickness.

Scientific reports·2026
Same author

Xinfeng Capsule combined with conventional Western medicine for rheumatoid arthritis: Efficacy, safety, and subgroup analysis in a multicenter real-world study.

Medicine·2026
Same author

An mRNA Tumor Nanovaccine Expressing Tumor Antigen Fused With Angiotensin II Facilitates Type 1 Conventional Dendritic Cell-Mediated Anti-Tumor Immunity.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Dynamic frailty trajectories, multidimensional resilience, and risk of incident hip fracture: A prospective cohort study with competing risk analysis.

Archives of gerontology and geriatrics·2026
Same author

The impact of growth hormone therapy on ocular structural parameters in idiopathic short stature: a systematic review and meta-analysis.

European journal of pediatrics·2026
Same author

Hypoxia-induced XBP1s-MYDGF axis suppresses ferroptosis through UBQLN1-mediated stabilization of LCN2 in gastric cancer.

Oncogene·2026
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
查看所有相关文章

相关实验视频

Updated: Jun 27, 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

使用监督机器学习从病理样本分类单细胞PBMC类型的协议.

Minjie Lyu1, Lin Xin1, Huan Jin1

  • 1School of Computer Science, University of Nottingham, Ningbo, Zhejiang, China.

Methods in molecular biology (Clifton, N.J.)
|May 31, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种机器学习协议,用于使用单细胞转录学数据准确分类外围血液单核细胞 (PBMC). 这种方法增强了疾病分类和病态状态的治疗评估.

关键词:
细胞类型分类 细胞类型分类疾病 疾病 疾病周围血液中的单核细胞.协议 协议 协议 协议 协议单细胞转录组学 单细胞转录组学有监督的机器学习.

更多相关视频

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.6K
Author Spotlight: Advancements in PBMC Isolation – Enhancing Throughput and Consistency in Research
06:23

Author Spotlight: Advancements in PBMC Isolation – Enhancing Throughput and Consistency in Research

Published on: July 19, 2024

3.5K

相关实验视频

Last Updated: Jun 27, 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
Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.6K
Author Spotlight: Advancements in PBMC Isolation – Enhancing Throughput and Consistency in Research
06:23

Author Spotlight: Advancements in PBMC Isolation – Enhancing Throughput and Consistency in Research

Published on: July 19, 2024

3.5K

科学领域:

  • 免疫学 免疫学 免疫学
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • 周围血液单核细胞 (PBMC) 对于研究免疫系统,疾病和疫苗至关重要.
  • 单细胞转录组学 (SCT) 可以通过基因表达来识别细胞类型,但通常依赖于复杂的手动分类方法.
  • 准确的细胞类型分类对于疾病诊断和评估治疗疗效至关重要.

研究的目的:

  • 在SCT数据上使用监督机器学习 (ML) 来分类PBMC细胞类型的协议.
  • 为了从病理样本中高精度和高效地分类PBMC.
  • 为各种SCT平台提供适用的框架,包括10×基因组学.

主要方法:

  • 该协议涉及三个关键阶段:数据预处理,在标记的PBMC SCT数据集上训练监督的ML模型,并将这些模型应用于新的疾病样本.
  • 使用监督机器学习算法进行细胞类型分类.
  • 专注于单细胞转录组学数据分析.

主要成果:

  • 开发的协议在分类PBMC细胞类型方面实现了高准确性和效率.
  • 证明了监督ML在分析复杂的SCT数据方面的有效性.
  • 该方法可以适应不同的SCT平台.

结论:

  • 监督机器学习为从SCT数据进行PBMC分类提供了一种强大而高效的方法.
  • 该协议有助于更精确的疾病分类和治疗评估.
  • 该方法广泛适用于来自各种来源和技术的SCT数据集.