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

Regulated mRNA Transport02:22

Regulated mRNA Transport

6.2K
In eukaryotes, transcription and translation are compartmentalized; an mRNA is first synthesized in the nucleus and then selectively transported to the cytoplasm for protein synthesis. Before transport, a pre-mRNA undergoes several steps of post-transcriptional modifications including splicing, 5' capping, and the addition of a poly-adenine tail. Various proteins bind to the pre-mRNA during these modifications. The mRNA transport takes place with the help of multiple proteins playing...
6.2K
Ribosome Profiling02:24

Ribosome Profiling

3.4K
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...
3.4K
Nucleic Acids02:43

Nucleic Acids

43.2K
Nucleic acids are the most important macromolecules for the continuity of life. They carry the cell's genetic blueprint and carry instructions for its functioning.
DNA and RNA
The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA is the genetic material in all living organisms, ranging from single-celled bacteria to multicellular mammals. It is in the nucleus of eukaryotes and in the organelles, chloroplasts, and mitochondria. In prokaryotes,...
43.2K
The Nucleolus02:55

The Nucleolus

8.6K
The nucleolus is the most prominent substructure of the nucleus. When it was first discovered, it was considered to be an isolated organelle that forms fibrils and granules. In 1931, the relationship between the nucleolus and chromosomes was first described by Heitz. He observed that the appearance and size of nucleolus varies depending on the stage of the cell cycle. He also noticed constricted regions on different chromosomes clustered together at definite cell cycle stages. These regions,...
8.6K
Leaky Scanning02:28

Leaky Scanning

5.0K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.0K
RNA Splicing01:32

RNA Splicing

55.9K
Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
55.9K

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 disentangled transformer-based transfer learning framework to predict patient drug response from tumor single-cell transcriptomics.

Bioinformatics (Oxford, England)·2026
Same author

FluNexus: A versatile web platform for antigenic prediction and visualization of influenza A viruses.

iMeta·2026
Same author

Mosaic integration of spatial multi-omics with SpaMosaic.

Nature genetics·2026
Same author

Artificial Intelligence Powers Protein Functional Annotation.

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

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction.

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

MotifGT-DTI: Pivotal Motif-Based Graph Transformer Model Improves Drug--Target Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026

相关实验视频

Updated: May 21, 2025

Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells
05:27

Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells

Published on: June 16, 2023

1.3K

RNALoc-LM:使用预训练的RNA语言模型进行RNA亚细胞局部化预测.

Min Zeng1, Xinyu Zhang1, Yiming Li1

  • 1School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China.

Bioinformatics (Oxford, England)
|March 22, 2025
PubMed
概括

新型深度学习框架RNALoc-LM使用预训练的RNA语言模型准确预测RNA亚细胞局部化. 这种方法的性能优于现有的工具,有助于发现重要的RNA动机.

更多相关视频

Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection
07:35

Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection

Published on: August 6, 2019

6.0K
Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells
10:24

Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells

Published on: December 17, 2012

14.3K

相关实验视频

Last Updated: May 21, 2025

Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells
05:27

Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells

Published on: June 16, 2023

1.3K
Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection
07:35

Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection

Published on: August 6, 2019

6.0K
Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells
10:24

Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells

Published on: December 17, 2012

14.3K

科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 分子生物学分子生物学

背景情况:

  • 准确预测RNA亚细胞定位对于理解RNA功能和调节至关重要.
  • 现有的计算方法往往专注于单一的RNA类型,留下多种类型预测的空白.
  • 预训练的RNA语言模型在生物信息学中表现有前途,但在亚细胞局部化预测中未得到充分利用.

研究的目的:

  • 开发一种可解释的深度学习框架,用于预测RNA亚细胞局部化.
  • 利用预先训练的RNA语言模型来提高预测准确度.
  • 为了使多种RNA类型的同时预测.

主要方法:

  • 开发了RNALoc-LM,这是一个利用预训练的RNA语言模型进行序列编码的框架.
  • 采用TextCNN和BiLSTM模块来捕获RNA序列中的本地和远程依赖关系.
  • 纳入了多头注意力机制,以专注于关键的RNA区域.

主要成果:

  • RNALoc-LM显著超过了现有的深度学习基线和最先进的预测器.
  • 基因分析表明RNALoc-LM能够识别重要的RNA基因.
  • 一项废除研究验证了从预先训练的语言模型中嵌入RNA序列的有效性.

结论:

  • RNALoc-LM在预测RNA亚细胞局部化方面取得了重大进展.
  • 该框架的可解释性和性能突出显示了预训练的RNA语言模型在这个领域的潜力.
  • 在RNA生物学中,RNALoc-LM为预测和发现基因提供了一个强大的工具.