Search research articles

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 Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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

Hematopoietic stem and progenitor cells derived platelet lysate promotes diabetic wound healing.

Molecular medicine (Cambridge, Mass.)·2026

Same author

A regenerative and programmable iPSC-derived platelet platform for universal drug delivery and immunotherapy.

Trends in biotechnology·2026

Same author

Retraction Note: The gut-lung axis and microbiome dysbiosis in non-tuberculous mycobacterial infections: immune mechanisms, clinical implications, and therapeutic frontiers.

Gut pathogens·2026

Same author

Comparative dosimetric and radiobiological assessment of a hybrid-VMAT strategy incorporating supplemental short-arcs for left-sided postmastectomy radiotherapy.

Frontiers in oncology·2026

Same author

HisCMCL: Cross-Modal Contrastive Learning with Hierarchical Multi-Scale Fusion for Spatial Expression Prediction.

Bioinformatics (Oxford, England)·2026

Same author

Qilin Pills protect against diminished ovarian reserve by suppressing pathological overactivation of PINK1/Parkin-mediated mitophagy in granulosa cells.

Journal of ethnopharmacology·2026

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

Search research articles

相关实验视频

Updated: Jun 8, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

SpaDiT:使用scRNA-seqq进行空间基因表达预测的扩散变压器.

Xiaoyu Li¹, Fangfang Zhu², Wenwen Min¹

¹School of Information Science and Engineering, Yunnan University, 650500, Kunming, Yunnan, China.

Briefings in bioinformatics

|November 7, 2024

概括

此摘要是机器生成的。

深度学习框架SpaDiT通过使用单细胞RNA测序数据预测基因表达来增强空间转录组学. 这种方法改善了在空间数据集中的组织结构和基因活性分析.

关键词:

扩散模型的扩散模型.基因表达预测基因表达在 scRNA-seq 数据中.空间转录组学数据数据变压器的变压器是一个变压器.

更多相关视频

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

相关实验视频

Last Updated: Jun 8, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

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:

空间解析转录组学 (SRT) 提供了对组织架构的洞察力,但捕获了有限的基因表达.
现有的SRT方法在高通量基因检测方面扎,限制了它们的应用价值.
在当前的空间转录组学 (ST) 数据集中,很大一部分基因表达仍然未被检测到.

研究的目的:

开发一个深度学习框架,SpaDiT,用于ST数据中准确的空间重建和基因表达预测.
为了利用单细胞RNA测序 (scRNA-seq) 数据作为提高ST数据分析的先决条件.
克服当前SRT技术中基因检测的局限性.

主要方法:

SpaDiT使用scRNA-seq数据作为先验信息.
在ST和scRNA-seq数据之间共享的基因被用作输入构建的潜在表示.
深度学习框架用于空间重建和基因表达预测.

主要成果:

SpaDiT显著提高了空间基因表达预测的准确性.
该框架在各种基于seq和基于图像的ST数据集中表现出有效性.
与八种基线方法相比,SpaDiT实现了8%-12%的性能改善.

结论:

SpaDiT有效地解决了在ST数据中有限的基因检测的挑战.
深度学习框架为推进空间转录学研究提供了有价值的工具.
SpaDiT为分析复杂的生物组织提供了更高的准确性和适用性.