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

DNA Microarrays02:34

DNA Microarrays

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...
Real Time RT-PCR02:57

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...
RNA-seq03:21

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 microarray-based...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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

AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes.

bioRxiv : the preprint server for biology·2026
Same author

Restoration of E-cadherin Expression Alters Metastatic Organotropism in Invasive Lobular Breast Carcinoma Models.

bioRxiv : the preprint server for biology·2026
Same author

Early-life mucosal T cells direct intestinal stem cell fate via a coordinated developmental program.

bioRxiv : the preprint server for biology·2026
Same author

RET signaling as a mediator of estrogen receptor positive breast cancer brain metastasis.

Communications biology·2026
Same author

Unraveling Tissue-Specific Molecular Signatures and Convergent Pathway Enrichments in Suicidal Behavior.

bioRxiv : the preprint server for biology·2026
Same author

Whole-genome doubling drives immune evasion by silencing antigen presentation.

Cancer cell·2026

相关实验视频

Updated: Jul 19, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K

在整合多个批量或单细胞转录组研究时,用于检测多类生物标志物的相互信息.

Jian Zou1, Zheqi Li2,3, Neil Carleton4,5,6

  • 1Department of Statistics, School of Public Health, Chongqing Medical University, Chongqing, Chongqing 400016, China.

Bioinformatics (Oxford, England)
|November 20, 2024
PubMed
概括

本研究介绍了相互信息对应分析 (MICA),这是一个用于检测生物标志物的新方法,用于在复杂的多类设计的多个omics研究中检测生物标志物. MICA提高了准确性,控制了错误的发现,提供了宝贵的生物学见解.

更多相关视频

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.1K
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

641

相关实验视频

Last Updated: Jul 19, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.1K
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

641

科学领域:

  • 生物医学研究的研究.
  • 生物信息学是一种生物信息学.
  • 基因组学就是基因组学.
  • 文字转录学 (Transcriptomics) 是一个学科.
  • 系统生物学 系统生物学

背景情况:

  • 生物标志物检测在生物医学研究中至关重要.
  • 整合多个omics研究可以提高生物标志物发现能力.
  • 现有的方法仅限于两类场景,而不是多类设计.

研究的目的:

  • 开发一个统计框架,用于检测具有一致的多类表达模式的生物标志物,跨多个omics研究.
  • 为了解决处理多类omics数据的现有方法的局限性.
  • 为复杂的生物系统中生物标志物发现提供强大而准确的方法.

主要方法:

  • 拟议的相互信息一致性分析 (MICA) 框架.
  • 利用基于相互信息的信息理论方法进行全球测试.
  • 实施了后期分析,以确定检测到的生物标志物的一致研究.
  • 将MICA应用于转录组和单细胞RNA-Seq数据.

主要成果:

  • 与模拟中现有的多类相关联方法相比,MICA证明了更好的准确性和有效的错误发现率控制.
  • 将MICA应用于小鼠的新陈代谢和雌激素治疗表达特征,揭示了重要的生物学见解.
  • 使用单细胞RNA-Seq数据在三阴性乳腺癌微环境中确定了核糖体功能的关键作用.

结论:

  • MICA提供了一个强大而通用的框架,用于在多类omics研究中检测生物标志物.
  • 该方法为整合各种生物数据集提供了更高的准确性和稳定性.
  • MICA具有发现新型治疗点和理解复杂疾病的潜力.