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相关概念视频

Epigenetic Regulation01:37

Epigenetic Regulation

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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
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相关实验视频

Updated: Sep 20, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
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通过深度学习预测表达改变促进子突变

Kishore Jaganathan1, Nicole Ersaro1, Gherman Novakovsky1

  • 1Illumina Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA, USA.

Science (New York, N.Y.)
|May 29, 2025
PubMed
概括

一个新的深度神经网络,PromoterAI,识别了导致罕见遗传疾病的非编码促进体变异. 这些变异影响基因表达,并处于负选择状态,解释了罕见疾病的遗传负担的6%.

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科学领域:

  • 遗传学
  • 生物信息学
  • 基因组学

背景情况:

  • 只有少数罕见的遗传疾病被诊断出来.
  • 在非编码DNA序列中可能存在未被识别的致病变体.

研究的目的:

  • 开发一个深度神经网络,PromoterAI,用于识别失调基因表达的非编码促进体变体.
  • 评估这些变异对基因表达及其在罕见疾病中的作用.

主要方法:

  • 开发了一种深度神经网络,用于预测表达改变的促进体变体.
  • 分析了成千上万个人的RNA和蛋白质表达数据.
  • 研究了对这些变体的负选择.
  • 使用报告测试验证功能影响.

主要成果:

  • 激发器AI准确地识别了非编码激发器变体.
  • 预测表达改变后果的变体显示异常表达水平.
  • 这些变种在人类群体中受到强烈的负面选择.
  • 罕见疾病患者的临床相关基因对这些变异具有丰富性.

结论:

  • 非编码促进体变异对罕见的遗传疾病有显著的贡献.
  • 促进器AI是诊断罕见遗传疾病的宝贵工具.
  • 发起者变异约占罕见疾病遗传负担的6%.