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

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

8.6K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
8.6K
Ribosome Profiling02:24

Ribosome Profiling

3.6K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.6K
Types of RNA01:20

Types of RNA

5.9K
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in regulating gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA Performs Diverse...
5.9K
RNA-seq03:21

RNA-seq

10.1K
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...
10.1K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.6K
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...
13.6K

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

Progress in understanding the infection mechanisms, soil microecological imbalance, and integrated control strategies of tobacco black shank.

Frontiers in microbiology·2026
Same author

Berberine Improved the Therapeutic Efficacy of UC-MSCs for DSS-Induced Colitis via Aerobic Glycolysis.

Phytotherapy research : PTR·2026
Same author

Molecular mechanisms of dissolved organic matter transformation and microbial interactions in composting.

Bioresource technology·2026
Same author

Discovery of small molecule inhibitors of liver X receptor for pediatric metabolic disorders by structure based screening, modelling, dft analysis and MD simulation.

Scientific reports·2026
Same author

An Inorganic Fiber-Polymer Composite-Based Quasi-Solid Electrolyte for High-Performance Electrochromic Devices.

ACS nano·2026
Same author

Preceding crops may reduce denitrification potential and enhance ammonium assimilation pathways.

Frontiers in microbiology·2026

相关实验视频

Updated: Jul 19, 2025

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA
09:36

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

25.4K

长非编码RNA研究:全基因组的方法.

Shuang Tao1, Yarui Hou1, Liting Diao1

  • 1The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China.

Genes & diseases
|August 9, 2023
PubMed
概括
此摘要是机器生成的。

本综述概述了研究长非编码RNA (lncRNAs) 的全基因组策略. 它涵盖了使用高级测序和生物信息学的识别,功能表征和机械研究.

关键词:
与癌症有关的 lncRNAs.计算管道的计算管道全基因组研究研究.长长的非编码RNAs.技术方法技术方法.

更多相关视频

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

2.5K
Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library
07:28

Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library

Published on: January 10, 2025

300

相关实验视频

Last Updated: Jul 19, 2025

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA
09:36

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

25.4K
Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

2.5K
Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library
07:28

Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library

Published on: January 10, 2025

300

科学领域:

  • 基因组学就是基因组学.
  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 长非编码RNAs (lncRNAs) 是具有重要生物作用的复杂分子.
  • 尽管进行了广泛的研究,但仍然有许多关于lncRNA复杂性和功能的未知.
  • 高通量技术和生物信息学的进步加速了ncRNA的发现.

研究的目的:

  • 为 lncRNAs.提供全基因组研究策略的全面概述.
  • 系统地引入用于lncRNA识别,功能表征和机制研究的方法.
  • 要突出在lncRNA研究中的实验和计算方法的整合.

主要方法:

  • 使用高通量测序和计算管道进行全基因组识别.
  • 通过表达图谱分析和基因组规模选进行功能性表征.
  • 机制研究采用大规模实验技术和计算分析.

主要成果:

  • 总结了用于lncRNA研究的主要实验方法和生物信息管道.
  • 详细的新 lncRNA 鉴定策略.
  • 概述了功能和机制研究的方法,包括与癌症相关的 lncRNAs.

结论:

  • 建立了全基因组lncRNA研究的系统概述.
  • 表示一个全面的 lncRNA 研究系统,整合了多种方法.
  • 强调了先进技术和生物信息学在推进 lncRNA 研究中的重要性.