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相关概念视频

Regulated mRNA Transport02:22

Regulated mRNA Transport

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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...
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Ribosome Profiling02:24

Ribosome Profiling

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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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Nuclear Protein Sorting01:34

Nuclear Protein Sorting

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Nuclear protein sorting is the selective trafficking of histones, polymerases, gene regulatory proteins into the nucleus and exporting RNAs and ribosomes to the cytosol. It is a tightly controlled process that regulates gene expression within a cell.
Proteins targeted to the nucleus carry nuclear localization signals or NLS recognized by import receptors in the cytosol. Similarly, proteins with nuclear export signals are recognized by export receptors. Import and export receptors are...
4.6K
Nuclear Localization Signals and Import01:46

Nuclear Localization Signals and Import

5.7K
Proteins targeted to the nucleus carry short stretches of amino acid sequences called the nuclear localization signal or NLS. Classical nuclear localization signals are of two types: monopartite and bipartite NLS. Monopartite classical NLS (cNLS) consists of a single cluster of 4-8 amino acids. Bipartite cNLS consists of two clusters of  2-3 amino acids and a 9-12 residue long proline-rich linker bridging the two clusters. Signal clusters are rich in positively charged amino acids such as...
5.7K
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

10.6K
The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
10.6K
Nuclear Export of mRNA02:31

Nuclear Export of mRNA

7.7K
Before mRNAs are exported to the cytoplasm, it is crucial to check each mRNA for structural and functional integrity. Eukaryotic cells use several different mechanisms, collectively known as mRNA surveillance, to look for irregularities in mRNAs. Irregular or aberrant mRNA are rapidly degraded by various enzymes. If a defective mRNA escapes the surveillance, it would be translated into a protein which would either be non-functional or not function properly. One of the primary irregularities in...
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相关实验视频

Updated: Jul 4, 2025

Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells
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Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells

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基于机器学习技术的统一mRNA亚细胞定位预测器.

Saleh Musleh1, Muhammad Arif1, Nehad M Alajez2,3

  • 1College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

BMC genomics
|February 7, 2024
PubMed
概括
此摘要是机器生成的。

预测信使RNA (mRNA) 亚细胞定位对于基因调节至关重要. 一个新的机器学习模型,UMSLP,为预测细胞中的mRNA位置提供了更快,更准确的in silico方法.

关键词:
机器学习是机器学习.多类分类的分类是多类分类.亚细胞定位 亚细胞定位它们是mRNARNA.

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相关实验视频

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Visualization of Endoplasmic Reticulum Localized mRNAs in Mammalian Cells
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Isolation of mRNAs Associated with Yeast Mitochondria to Study Mechanisms of Localized Translation
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Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells
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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:

  • 传递 RNA (mRNA) 的细胞下定位对于基因表达,细胞迁移和适应至关重要.
  • 确定mRNA局部化的实验方法是昂贵的,耗时的,劳动密集的.

研究的目的:

  • 开发一种高效准确的计算方法来预测mRNA亚细胞局部化.
  • 通过一种in silico方法来解决当前实验技术的局限性.

主要方法:

  • 利用一种基于机器学习 (ML) 的方法,命名为统一的mRNA亚细胞定位预测器 (UMSLP).
  • 采用一个包含四个特征集的in silico策略:kmer,伪k-tuple核酸组成,核酸物理化学属性和Z曲线转换.
  • 在五个不同的亚细胞区域的基准数据集上验证了模型:细胞核,细胞质,细胞外区域 (ExR),线粒体和内质网膜 (ER).

主要成果:

  • 在独立测试数据集上,UMSLP实现了高预测性能,精度超过87%,特异性超过94%,准确性超过94%.
  • 在平均预测准确度方面,UMSLP显著优于mRNALocator,mRNALoc和SubLocEP等现有工具.
  • 莎普利的添加式扩展揭示了k-mer特征在大多数局部化中占主导地位,而Z曲线特征对于线粒体预测至关重要.

结论:

  • UMSLP提供了一种强大而准确的工具,用于预测mRNA亚细胞局部化.
  • 开发的in silico方法为实验方法提供了一种具有成本效益和效率的替代方案.
  • 这项研究强调了综合特征集对于稳健预测mRNA定位的重要性.