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相关概念视频

RNA Splicing01:32

RNA Splicing

60.4K
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...
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Pre-mRNA Processing: RNA Splicing01:36

Pre-mRNA Processing: RNA Splicing

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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Alternative RNA Splicing02:18

Alternative RNA Splicing

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Alternative RNA Splicing02:18

Alternative RNA Splicing

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Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
24.7K

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相关实验视频

Updated: Jan 17, 2026

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
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Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

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通过使用深度学习来建模拼接站点来改善拼接对齐.

Siying Yang1,2, Neng Huang1,2, Heng Li1,2,3

  • 1Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02215, USA.

ArXiv
|September 22, 2025
PubMed
概括
此摘要是机器生成的。

这项研究介绍了 minisplice,一种使用卷积神经网络的新方法,以提高RNA和蛋白质序列的拼接对齐精度. 它增强了基因注释和功能研究,特别是在有噪音数据的情况下.

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

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Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection
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Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection

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Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Analysis of Spliceosomal snRNA Localization in Human Hela Cells Using Microinjection
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科学领域:

  • 基因组学就是基因组学.
  • 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:

  • 拼接对齐对于基因注释和功能研究至关重要.
  • 目前的方法使用简单的拼接位置模型,限制了不同序列的准确性.

研究的目的:

  • 开发一个复杂的模型,用于拼接部位检测.
  • 为了提高生物信息学中的拼接对齐的准确性.

主要方法:

  • 实施了迷你拼接,1D-CNN模型,对脊椎动物和昆虫基因组的7026个参数进行了训练.
  • 估计GT/AG二核酸的经验拼接概率.
  • 修改了minimap2和miniprot以结合拼接概率.

主要成果:

  • 该模型捕获了跨类的保存拼接信号,并识别了哺乳动物和鸟类中的富含GC的内核.
  • 在长时间读取的人类RNA-seq数据上观察到更好的连接精度.
  • 实现了对具有遥远同质性的蛋白质的更高准确性.

结论:

  • 迷你拼接显著提高了拼接对齐的准确性,特别是在具有挑战性的数据集.
  • 这一进步有助于基因注释和功能基因组学研究.