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相关概念视频

Long-patch Base Excision Repair01:02

Long-patch Base Excision Repair

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Since the discovery of the two BER pathways, there has been a debate about how a cell chooses one pathway over the other and the factors determining this selection. Numerous in vitro experiments have pointed out multiple determinants for the sub-pathway selection. These are:
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RACE - Rapid Amplification of cDNA Ends02:35

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines
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深度双重增强器:一种基于DNABert的双重功能输入深度学习方法,用于增强器识别.

Tao Song1, Haonan Song1, Zhiyi Pan1

  • 1Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum, Qingdao 266555, China.

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|November 9, 2024
PubMed
概括
此摘要是机器生成的。

DeepDualEnhancer使用DNA序列和基因组信号准确识别增强剂. 这种新的深度学习方法优于现有的增强器识别方法.

关键词:
DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert DNABert深度学习是一种深度学习.增强剂是一种增强剂.这是基因组信号.

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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:

  • 增强剂是控制基因表达的关键 cis 调节性 DNA 元素.
  • 鉴定增强剂由于其复杂的序列特征而具有挑战性.

研究的目的:

  • 为准确的增强器识别开发一个强大的深度学习模型.
  • 研究基因组信号在增强增强器识别方面的实用性.

主要方法:

  • 提出了DeepDualEnhancer,这是一种基于DNABert的方法,利用多尺度卷积神经网络 (CNN) 和BiLSTM进行DNA序列分析.
  • 开发了DeepDualEnhancer-genomic,将基因组信号与变压器序列注意力结合起来,用于增强特征提取.
  • 利用了广泛的数据集和严格的验证,包括5倍交叉验证和独立测试.

主要成果:

  • 与其他20种方法相比,DeepDualEnhancer表现出优越的性能.
  • 纳入基因组信号显著提高了增强器识别准确度.
  • 废弃性研究证实了单个模型组件的有效性.

结论:

  • DeepDualEnhancer为增强器识别提供了一个强大而准确的解决方案.
  • 整合基因组信号有利于改善增强器识别任务.
  • 这些发现推动了调控基因组学和基因表达分析领域的发展.