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

Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

1.9K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
1.9K
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

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

SpecEStop: Self-Supervised Hyperspectral Mixed Noise Removal via Deep Spectral Prior.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Local and High-Order Consistency Coding and Adaptation for Cross-Hypergraph Node Classification.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Separable Decomposition for Ragged Tensors.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Nonlinear Transformed Low-Rank Quaternion Tensor Total Variation for Multidimensional Color Image Completion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Low-Rank Tensor Learning by Generalized Nonconvex Regularization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

DELTA: Deep Low-Rank Tensor Representation for Multi-Dimensional Data Recovery.

IEEE transactions on pattern analysis and machine intelligence·2025
Same journal

STED: flexible cross-modal topic modeling infers cell-type-specific regulatory landscapes from bulk epigenomics.

Briefings in bioinformatics·2026
Same journal

A knowledge-guided deep learning framework for quantitative nucleic acid testing.

Briefings in bioinformatics·2026
Same journal

Optimal transport for label transfer in single-cell multi-omics integration.

Briefings in bioinformatics·2026
Same journal

Continuous multi-omics pathway enrichment analysis resolves hidden functional heterogeneity.

Briefings in bioinformatics·2026
Same journal

Evaluating completeness, coherence, and consistency of genome-scale function annotations.

Briefings in bioinformatics·2026
Same journal

Transformers for single-cell RNA sequencing: a survey.

Briefings in bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: Jun 5, 2025

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

18.4K

GSTRPCA:对于单单细胞多omics数据集群的不规则张量奇数值分解.

Lubin Cui1, Guiliang Guo1, Michael K Ng2

  • 1School of Mathematics and Statistics, Henan Normal University, Xinxiang 453007, China.

Briefings in bioinformatics
|December 16, 2024
PubMed
概括
此摘要是机器生成的。

我们介绍了GSTRPCA,这是一种用于整合单细胞多omics数据的新型张量分解方法. 这种方法保留了数据结构,并通过揭示不同omics层之间的隐藏关系来增强聚类性能.

关键词:
不规则的张量分解.关节张力器 关节张力器单单细胞多omics数据数据有权重的门值.

更多相关视频

Author Spotlight: Deciphering the Cellular Mysteries of Intermuscular Adipose Tissue in Humans
05:59

Author Spotlight: Deciphering the Cellular Mysteries of Intermuscular Adipose Tissue in Humans

Published on: May 3, 2024

590
Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level
09:45

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Published on: March 14, 2022

2.9K

相关实验视频

Last Updated: Jun 5, 2025

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

18.4K
Author Spotlight: Deciphering the Cellular Mysteries of Intermuscular Adipose Tissue in Humans
05:59

Author Spotlight: Deciphering the Cellular Mysteries of Intermuscular Adipose Tissue in Humans

Published on: May 3, 2024

590
Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level
09:45

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Published on: March 14, 2022

2.9K

科学领域:

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

背景情况:

  • 单细胞多omics数据集成对于理解细胞复杂性至关重要.
  • 现有的方法难以处理多样化的特征维度和保存数据结构.
  • 需要有效的整合模型来提取隐藏的关系.

研究的目的:

  • 为不规则的单细胞多组数据提出一种新的张量分解模型.
  • 开发一种在集成过程中保留原始数据结构的方法.
  • 通过探索隐藏的特性来提高集群性能.

主要方法:

  • 开发了一个不规则的张量分解模型 (GSTRPCA) 基于张量强主要组件分析 (TRPCA).
  • 采用加权值模型,对不规则张量数据使用低等级和稀疏度约束.
  • 设计了一种具有全球融合理论保障的算法.

主要成果:

  • GSTRPCA有效地保留了多omics数据集的原始数据结构.
  • 该方法成功地揭示了不同omics数据中隐藏的相关特征.
  • 计算实验表明,GSTRPCA在聚类单细胞多组数据方面显著超过了最先进的方法.

结论:

  • GSTRPCA是用于不规则数据的第一个张量分解方法,它保持了结构并改善了聚类.
  • 该算法为单细胞多omics数据集成提供了一个强大的新工具.
  • 基于MATLAB的代码是公开可用的,用于研究.