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相关概念视频

RNA Splicing01:32

RNA Splicing

56.5K
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...
56.5K
Pre-mRNA Processing: RNA Splicing01:36

Pre-mRNA Processing: RNA Splicing

5.3K
5.3K
Alternative RNA Splicing02:18

Alternative RNA Splicing

21.2K
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...
21.2K
Chromatin Structure and RNA Splicing02:41

Chromatin Structure and RNA Splicing

2.7K
2.7K
Chromatin Structure Regulates pre-mRNA Processing02:41

Chromatin Structure Regulates pre-mRNA Processing

7.0K
In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
7.0K
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...
9.0K

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相关实验视频

Updated: Jul 14, 2025

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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解读RNA拼接逻辑与可解释的机器学习.

Susan E Liao1, Mukund Sudarshan1, Oded Regev1

  • 1Department of Computer Science, Courant Institute of Mathematical Sciences, New York University, New York, NY 10012.

Proceedings of the National Academy of Sciences of the United States of America
|October 5, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一个可解释的神经网络用于RNA拼接,与最先进的精度相匹配. 该模型揭示了对拼接机制的新见解,并通过可解释的机器学习推动了科学发现.

关键词:
通过RNA拼接进行RNA拼接.人工智能的人工智能是人工智能.可以解释的机器学习.

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Using the E1A Minigene Tool to Study mRNA Splicing Changes
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相关实验视频

Last Updated: Jul 14, 2025

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

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

Published on: December 9, 2016

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Using the E1A Minigene Tool to Study mRNA Splicing Changes
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Using the E1A Minigene Tool to Study mRNA Splicing Changes

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A Reporter Based Cellular Assay for Monitoring Splicing Efficiency
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A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

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科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 机器学习 机器学习

背景情况:

  • 机器学习,特别是神经网络,加速科学发现,但往往缺乏可解释性.
  • 当前的神经网络无法解释它们的预测,阻碍了科学理解.
  • RNA拼接对于将基因组信息转化为功能产品至关重要.

研究的目的:

  • 为RNA拼接分析提供一个可解释的设计神经网络模型.
  • 为了实现与最先进的模型可比的预测准确性,同时提供洞察力.
  • 通过可解释机器学习来推进科学发现.

主要方法:

  • 开发了一个可解释的神经网络架构.
  • 在大型数据集上训练模型,用于RNA拼接预测.
  • 引入了一个可视化工具来追踪模型的决策过程.

主要成果:

  • 可解释模型实现了与最先进的方法相匹配的预测准确性.
  • 一种新的可视化允许从输入序列到输出序列追踪预测.
  • 该模型确定了RNA拼接逻辑的以前未被描述的组件.

结论:

  • 可解释机器学习可以提供重要的科学见解.
  • 开发的模型成功阐明了RNA拼接机制.
  • 这种方法通过使复杂模型易于理解来推动科学发现.