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相关概念视频

Mutations01:39

Mutations

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Overview
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Viral Mutations00:36

Viral Mutations

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Mismatch Repair01:20

Mismatch Repair

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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
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Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
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Translation01:31

Translation

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Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Proteins are...
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In-vitro Mutagenesis01:16

In-vitro Mutagenesis

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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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相关实验视频

Updated: Jul 5, 2025

In Vivo Modeling of the Morbid Human Genome using Danio rerio
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In Vivo Modeling of the Morbid Human Genome using Danio rerio

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误解突变的致病性分类基于深度生成模型.

Ke Bai1, Lu Yang1, Jian Xue1

  • 1Shandong Jianzhu University, Jinan, 250101, PR China.

Computers in biology and medicine
|January 19, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了MLAE,这是一种深度学习模型,可以准确识别与疾病相关的误解突变并预测它们的致病性. MLAE增强了用于疾病研究的蛋白质变体分析.

关键词:
深度生成模型的模型.多重标签分类的分类方法病原性分类的病原性分类.单氨基酸变异的变化变量自动编码器变量自动编码器

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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:

  • 人类蛋白质中的错误突变与各种疾病有关.
  • 这些突变的准确识别和致病性分类对于了解疾病机制和蛋白质功能至关重要.

研究的目的:

  • 提出MLAE (基于LSTM-LadderAutoEncoder的方法),这是一个新的深度学习模型,用于识别与疾病相关的误解突变并对其致病性进行分类.
  • 利用变异自动编码器 (VAE) 框架与LSTM网络和梯子结构来改善信息保留和模型学习.

主要方法:

  • 在VAE框架内开发了MLAE,这是一个集成LSTM网络和梯子结构的深度学习模型.
  • 应用了MLAE来对三个输入蛋白质分类所有27,572种可能的误解变异.

主要成果:

  • 获得了0.941的平均分类AUC,证明了MLAE在预测病原性方面的有效性.
  • 在多标签分类中获得了0.196的平均哈明斯损失,表明了对复杂变体的分类能力.

结论:

  • MLAE有效地捕获氨基酸序列信息,以准确预测误解突变的病原性.
  • 该模型为研究遗传疾病基础和疾病预防策略提供了有价值的分析工具.