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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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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
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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.
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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.
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  • 1State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.

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概括
此摘要是机器生成的。

我们开发了ncProFormer,这是一个深度学习工具,用于识别能够编码的非编码RNA (ncRNA). 这个框架准确地预测了微的功能,超过了现有的方法,并证明了跨物种的适用性.

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科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 分子生物学分子生物学

背景情况:

  • 非编码RNAs (ncRNAs) 可以转化为功能性微,但识别能够编码的ncRNAs是具有挑战性的.
  • 弱的翻译信号,低的保存率和数据异质性使准确的预测变得复杂.

研究的目的:

  • 开发一个先进的深度学习框架,ncProFormer,用于预测ncRNAs的编码潜力.
  • 提高识别功能性微编码ncRNA的准确性和通用性.

主要方法:

  • ncProFormer集成了GENA-LM核酸语言模型用于上下文序列嵌入.
  • 一个卷积神经网络 (CNN) 增强的变压器编码器捕获本地和远程序列依赖.
  • 该框架使用全代币表示策略进行全面分析.

主要成果:

  • ncProFormer在人类,外部验证和公共基准数据集上显著优于现有的方法.
  • 该模型在没有重新训练的情况下,在物种 (人类,老鼠,老鼠) 中表现出强大的预测性能.
  • 这突显了学习到的生物表征的可转移性和对分布变化的稳定性.

结论:

  • ncProFormer是一个有效和可泛化的深度学习框架,用于识别编码能力强的ncRNA.
  • 该工具提供了一种有前途的计算方法,用于在各种转录学背景下表征ncRNA函数.
  • 这项工作推进了ncRNA研究领域,通过提供一种可靠的方法来发现新的微编码ncRNA.