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相关概念视频

RNA Editing02:23

RNA Editing

9.0K
RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
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RNA Stability01:53

RNA Stability

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Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
33.7K
RNA Structure01:23

RNA Structure

71.6K
Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
71.6K
Pre-mRNA Processing: Modification of pre-mRNA Ends01:35

Pre-mRNA Processing: Modification of pre-mRNA Ends

9.5K
In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a cap to the 5' end of the growing transcript. In this process, a 5' phosphate is replaced by modified guanosine that has a methyl group attached (7-methyl guanosine). This 5' cap helps...
9.5K
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
Experimental RNAi02:15

Experimental RNAi

6.2K
RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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相关实验视频

Updated: Jul 20, 2025

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications
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2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications

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Rm-LR:一种基于远程的深度学习模型,用于预测多种类型的RNA修饰.

Sirui Liang1, Yanxi Zhao1, Junru Jin1

  • 1School of Software, Shandong University, Jinan, 250101, China; Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, 250101, China.

Computers in biology and medicine
|July 29, 2023
PubMed
概括

一种新的深度学习方法,Rm-LR,只使用RNA序列准确预测十种类型的RNA修饰. 这种方法利用预先训练的RNA语言模型和注意力网络,在识别RNA修饰位点方面提供卓越的性能.

关键词:
双线性注意力网络是一个双线性注意力网络.深度学习是一种深度学习.长距离的序列是远程的.预先训练的模型模型.基因组RNA的修饰是RNA的修饰.

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2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications

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Characterizing RNA Modifications in Single Neurons Using Mass Spectrometry
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科学领域:

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

背景情况:

  • RNA转录后修改对于调节基因表达和功能至关重要.
  • 准确识别RNA修饰部位对于理解RNA生物学至关重要.

研究的目的:

  • 开发一种新且准确的计算方法,用于预测多种类型的RNA修饰.
  • 利用深度学习和RNA语言模型来提高预测准确度.

主要方法:

  • 拟议的Rm-LR方法使用基于长距离的深度学习方法.
  • 整合了两种大型RNA语言预训练模型,以捕获序列和局部特征.
  • 集成功能使用双线性注意网络进行预测.

主要成果:

  • 仅使用RNA序列,Rm-LR可以准确预测十种RNA修饰类型 (m6A,m1A,m5C,m5U,m6Am, Ψ,Am,Cm,Gm,Um).
  • 在基准数据集上显著超过了最先进的方法.
  • 在各种RNA修饰中表现出强大的适应性和稳健性.

结论:

  • Rm-LR为RNA修饰预测提供了一种有效和卓越的计算模型.
  • 预先训练有素的RNA语言模型增强了对生物序列表示和模型解释性的学习.
  • 这项工作推进了RNA修饰的准确和可靠预测,为其复杂的景观提供了洞察力.