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相关概念视频

Nucleic Acid Structure01:25

Nucleic Acid Structure

5.9K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
5.9K
Nucleic Acids02:43

Nucleic Acids

43.4K
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,...
43.4K
Ribosome Profiling02:24

Ribosome Profiling

3.5K
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...
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相关实验视频

Updated: May 29, 2025

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

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一个深度学习模型,用于从单基分辨率的序列中描述蛋白质-RNA相互作用.

Xilin Shen1,2,3, Yayan Hou4,3, Xueer Wang5

  • 1Tianjin Cancer Institute, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.

Patterns (New York, N.Y.)
|February 3, 2025
PubMed
概括

根据序列数据,深度学习模型Reformer准确地预测蛋白质-RNA结合亲和力. 它确定了新的结合动机,改善了对RNA调节和突变影响的理解.

关键词:
在RBP中使用RBP.RNA结合蛋白质是RNA结合的蛋白质.RNA与蛋白质的相互作用深度学习是一种深度学习.这就是eCLIP-seqq.发现动机 发现动机图案的丰富 图案的丰富突变效应是一种突变效应.病原性变体的病原性变体单一基准解决方案的解决方案变压器变压器变压器变压器

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iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution
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iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

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Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
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Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

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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.
  • 基因组学就是基因组学.

背景情况:

  • 蛋白质-RNA相互作用对于基因表达和RNA代谢至关重要.
  • 了解这些相互作用是解读疾病中RNA失调的关键.
  • 目前用于表征蛋白-RNA结合的方法在分辨率和模式发现方面存在局限性.

研究的目的:

  • 从序列数据开发一个深度学习模型来预测蛋白质-RNA结合亲和力.
  • 识别新的RNA结合动机,并了解它们的功能相关性.
  • 改善RNA-蛋白相互作用的预测解决方案,并优先考虑与疾病相关的突变.

主要方法:

  • 开发了Reformer,这是一个深度学习模型,利用序列数据进行绑定亲和力预测.
  • 在225个增强交叉链接和免疫沉降测序 (eCLIP-seq) 数据集上接受过培训的改革者.
  • 使用电泳运动移动转移试验 (EMSAs) 验证的模型预测.

主要成果:

  • 在单基分辨率下,Reformer在预测蛋白质-RNA结合亲和力方面取得了很高的准确性.
  • 该模型确定了传统eCLIP-seq方法无法检测的RNA结合动机.
  • 学习的动机与RNA处理功能的相关性被证明.
  • 欧洲环境安全局证实了Reformer在量化对RNA调节突变影响的准确性.

结论:

  • 改革者增强了RNA-蛋白相互作用的预测分辨率.
  • 该模型有助于识别功能性RNA结合动机,并优先考虑影响RNA调节的突变.
  • 这种深度学习方法为研究RNA生物学和疾病机制提供了强大的工具.