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

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

Double emulsions enable in situ generation of permeation enhancers for oral delivery of macromolecules.

Journal of colloid and interface science·2026
Same author

BRIDGING THE GAP: ENHANCING THE GENERALIZABILITY OF EPIGENETIC CLOCKS THROUGH TRANSFER LEARNING.

The annals of applied statistics·2026
Same author

McCune-Albright Syndrome with Extensive Fibrous Dysplasia Evaluated by 18F-FDG PET/CT and Whole-body Bone Scintigraphy: A Case Report.

Nuklearmedizin. Nuclear medicine·2026
Same author

Xanthomonas Type III Effector XopN Targets Scaffold Protein OsRACK1B to Suppress Rice Immunity.

Molecular plant pathology·2026
Same author

Pan-cancer spatial atlas of tertiary lymphoid structures.

Science (New York, N.Y.)·2026
Same author

Iodide Anion Anchoring by Silver Nanoparticles Enables Shuttle-Free Zinc-Iodine Batteries.

Angewandte Chemie (International ed. in English)·2026
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
查看所有相关文章

相关实验视频

Updated: Jun 17, 2025

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment
06:05

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

7.3K

空间CTD:一个大规模的瘤微环境空间转录组数据集,用于评估免疫瘤学细胞类型解.

Jiayuan Ding1, Lingxiao Li2, Qiaolin Lu3

  • 1Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, USA.

Journal of computational biology : a journal of computational molecular cell biology
|August 8, 2024
PubMed
概括
此摘要是机器生成的。

一个新的大规模数据集,空间CTD和一个图形神经网络方法,GNNDeconvolver,在人类免疫瘤学空间转录学中推进细胞类型的解卷. 使用这种现实的基准,GNNDeconvolver显著优于现有方法.

关键词:
基准数据集是一个基准数据集.细胞类型的解解.图形神经网络的神经网络人类免疫瘤学空间转录组数据的空间转录组数据瘤微环境是一个微环境.

更多相关视频

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.1K
Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment
10:13

Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment

Published on: June 21, 2022

2.2K

相关实验视频

Last Updated: Jun 17, 2025

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment
06:05

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

7.3K
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.1K
Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment
10:13

Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment

Published on: June 21, 2022

2.2K

科学领域:

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

背景情况:

  • 空间分辨率的转录形状分析提供了具有成本效益的多细胞分辨率.
  • 细胞类型的解卷对于分析空间数据中的混合细胞群体至关重要.
  • 现有的基准是有限的,通常是模拟的,以小鼠为基础的,不适合人类免疫瘤学.

研究的目的:

  • 介绍 SpatialCTD,这是一个大规模的基准数据集,用于人类免疫瘤学空间转录体解卷.
  • 开发和验证GNNDeconvolver,一种用于细胞类型解卷的新型图形神经网络方法.
  • 提供一种可访问的工具,用于将多样化的空间转录数据转换为标准化的伪点.

主要方法:

  • 使用来自人类瘤微环境 (肺,脏,肝脏) 的180万个细胞和12900个伪点构建空间CTD数据集.
  • 开发GNNDeconvolver,一个利用位置感知参考数据的图形神经网络.
  • 对最先进的解卷方法进行比较性绩效评估.

主要成果:

  • 与单细胞RNA测序 (scRNA-seq) 衍生引用相比,空间CTD为解卷提供了更现实的引用.
  • 在细胞类型解方面,GNNDeconvolver在现有方法中表现出优越的性能.
  • 拟议的方法在不依赖scRNA-seq数据的情况下实现了高精度.

结论:

  • 空间CTD和GNNDeconvolver为推进人类免疫瘤学中细胞类型解提供了一个强大的框架.
  • 开发的工具有助于在各种平台上全面评估和分析空间转录组数据.
  • 这项工作解决了当前基准数据集和解卷方法的关键局限性.