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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.3K
DNA Microarrays02:34

DNA Microarrays

20.6K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
20.6K
Multiple Allele Traits01:49

Multiple Allele Traits

37.9K
The Concept of Multiple Allelism
37.9K
Genomics02:02

Genomics

39.6K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
39.6K

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

A Theoretical Understanding of both Activity and Stability Promotion of NiFe-Based OER Catalysts via 3d-2p-4f Orbital Hybridization.

The journal of physical chemistry letters·2026
Same author

Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

How biological sex shapes differences in immune responses to infection.

Biology of sex differences·2026
Same author

Decoding immunotherapy response through computational modeling.

Nature communications·2026
Same author

Chatbot Usability Scale in Chinese Users: Cross-Cultural Adaptation and Validation Study.

JMIR human factors·2026
Same author

The Influence Pathway of the Burden on Caregivers of Children With Congenital Ear Malformations: An Analysis of the Mediating Effects of Social Support and Coping Mechanisms.

The Journal of craniofacial surgery·2026
Same journal

Correction to 'scSuperAnnotator: A platform for benchmarking comparison and visualizing automated cellular annotation methods for scRNA-seq data'.

Nucleic acids research·2026
Same journal

Correction to 'Differentiable partition function calculation for RNA'.

Nucleic acids research·2026
Same journal

Deployment of non-canonical splicing in tunicate genomes is mediated by divergent U2AF function and changing m6A modification in U1 and U6 snRNA.

Nucleic acids research·2026
Same journal

Bacillus subtilis DnaB forms multiple protein-protein interactions essential for DNA replication initiation.

Nucleic acids research·2026
Same journal

Multiple forms of protein-protein and DNA binding are exhibited by BrxC from the BREX phage restriction system.

Nucleic acids research·2026
Same journal

Biosynthesis of glycosylated 5-hydroxycytosine in the DNA of diverse viruses.

Nucleic acids research·2026
查看所有相关文章

相关实验视频

Updated: Jan 14, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

4.8K

空间2GWAS:一个数据库,用于将空间转录组区域与GWAS特征联系起来.

Xi Hu1, Aoqi Wang1, Huan Yu1

  • 1West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.

Nucleic acids research
|October 22, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了spatial2GWAS,这是一个数据库,将空间转录组区域与全基因组关联研究 (GWAS) 特征联系起来. 它揭示了组织基因表达模式如何影响复杂疾病,并确定了潜在的治疗点.

更多相关视频

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

649
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.3K

相关实验视频

Last Updated: Jan 14, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

4.8K
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

649
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.3K

科学领域:

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

背景情况:

  • 基因表达的空间异质性会影响生物功能和疾病的发病.
  • 空间解析的转录组与表型之间的系统关联,特别是在复杂的疾病中,尚未得到充分研究.

研究的目的:

  • 开发spatial2GWAS,这是一个全面的资源,将空间转录组 (ST) 区域与全基因组关联研究 (GWAS) 特征联系起来.
  • 为了能够系统地探索复杂特征背后的空间机制,并提供对特定区域的生物功能和治疗目标的见解.

主要方法:

  • 在五种技术和812个GWAS特征中收集了1196个ST切片 (人类和老鼠).
  • 确定了29701个ST切片-GWAS特征对,其中有47492个显著区域.
  • 对细胞类型组成,基因表达,通路激活和细胞-细胞通信进行功能分析.

主要成果:

  • 在特征相关和无关的空间区域之间观察到细胞类型组成,基因表达和通路激活的不同模式.
  • 空间2GWAS为可视化和高级查询提供了一个用户友好的界面.
  • 该数据库将ST数据与高级表型联系起来,促进对组织异质性的理解.

结论:

  • 空间2GWAS促进了对复杂特征的空间机制的系统研究.
  • 该资源有助于理解组织异质性在人类复杂疾病中的作用.
  • 确定了特定区域的生物功能和潜在的治疗点.