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

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

4.8K
4.8K
Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

7.5K
The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
7.5K
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

14.0K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
14.0K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

150
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
150

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

DiSCO: deconvoluting spatial transcriptomics via combinatorial optimization with a foundational diffusion model.

Briefings in bioinformatics·2026
Same author

BiCLUM: Bilateral contrastive learning for unpaired single-cell multi-omics integration.

PLoS computational biology·2026
Same author

CoFormerSurv: Collaborative transformer for multi-omics survival analysis.

PLoS computational biology·2026
Same author

SEPAR enables spatial metagene discovery and associated molecular pattern characterization in spatial transcriptomics and multi-omics datasets.

Communications biology·2025
Same author

Correction: Emerging strategies in colorectal cancer immunotherapy: enhancing efficacy and survival.

Frontiers in immunology·2025
Same author

Emerging strategies in colorectal cancer immunotherapy: enhancing efficacy and survival.

Frontiers in immunology·2025
Same journal

Combinatorial multiomic analysis from a pedigree of Sox10Dom Hirschsprung mice identifies multiple high confidence candidate modifiers of Enteric Nervous System development.

PLoS computational biology·2026
Same journal

Extracting host-specific developmental signatures from longitudinal microbiome data.

PLoS computational biology·2026
Same journal

Population sparseness determines strength of Hebbian plasticity for maximal memory lifetime in associative networks.

PLoS computational biology·2026
Same journal

Predictive coding explains asymmetric connectivity in the brain: A neural network study.

PLoS computational biology·2026
Same journal

Zooplankton feeding behavioral signatures in the morphology of macroscale prey spatial distribution.

PLoS computational biology·2026
Same journal

A brief overview of 20 years of neuroscience in PLoS Computational Biology.

PLoS computational biology·2026
查看所有相关文章

相关实验视频

Updated: Sep 17, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

OrgaCCC:在空间转录学数据上构建细胞-细胞通信网络的直角图形自编码器.

Xixuan Feng1, Shuqin Zhang2, Limin Li1

  • 1School of Mathematics and Statistics, Xi'an Jiaotong University, Shaanxi, China.

PLoS computational biology
|June 27, 2025
PubMed
概括
此摘要是机器生成的。

OrgaCCC是一种新的深度学习方法,通过空间转录组学数据增强了细胞间通信推断. 它通过整合基因表达,空间位置和配体-受体信息来提高准确性,以便更好地理解生物.

更多相关视频

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.1K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

915

相关实验视频

Last Updated: Sep 17, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.1K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

915

科学领域:

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

背景情况:

  • 细胞-细胞通信 (CCC) 对于多细胞生物的功能,组织平衡和适应至关重要.
  • 从空间转录组学 (ST) 数据中推断CCC机制是具有挑战性的,因为目前的计算方法的局限性依赖于不完整的基因相互作用列表.

研究的目的:

  • 开发一种先进的计算方法,OrgaCCC,从空间转录学数据中准确地推断细胞-细胞通信.
  • 通过利用全面的生物信息来克服现有方法的局限性.

主要方法:

  • 提出OrgaCCC,一个直角图自编码器方法,利用深度生成模型.
  • 综合基因表达特征,空间位置和连接体-受体关系.
  • 采用直角合变量图自编码器用于细胞/点和基因特征提取,并通过特征相似性最大化将它们结合起来.

主要成果:

  • 在五个ST数据集中,OrgaCCC在CCC推断方面表现优越,与最先进的方法相比.
  • 在细胞类型,细胞/点和体受体水平上实现了更高的准确性和可靠性.
  • 在空间背景下有效捕获复杂的细胞间通信模式.

结论:

  • OrgaCCC提供了一种强大而准确的方法,可以从空间转录学数据中推断细胞与细胞之间的通信.
  • 该方法通过改善对细胞间信号通路的理解,为生物过程提供了宝贵的见解.
  • OrgaCCC代表了计算生物学在分析复杂生物系统方面取得的重大进展.