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相关概念视频

Master Transcription Regulators02:23

Master Transcription Regulators

6.9K
Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
6.9K

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相关实验视频

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Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation
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Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

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增强剂-MDLF:一种新的深度学习框架,用于识别细胞特异增强剂.

Yao Zhang1, Pengyu Zhang2, Hao Wu1

  • 1School of Software, Shandong University, Jinan, 250100, Shandong, China.

Briefings in bioinformatics
|March 15, 2024
PubMed
概括

我们开发了Enhancer-MDLF,这是一种新的深度学习框架,用于识别增强剂,这些增强剂是调节基因转录的关键非编码DNA片段. 这种新方法在多个人类细胞系和数据集中显著优于现有的工具.

科学领域:

  • 基因组学就是基因组学.
  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 增强剂是关键的非编码DNA元素,可以调节基因转录.
  • 精确识别增强剂对于理解基因表达,调节网络和疾病机制至关重要.
  • 目前的增强剂识别方法有局限性,需要改进方法.

研究的目的:

  • 引入Enhancer-MDLF,这是一个新的多输入深度学习框架,用于准确识别增强器.
  • 评估Enhancer-MDLF与现有方法的性能.
  • 探索转移学习的应用,以增强特异性预测和模型解释以发现动机.

主要方法:

  • 开发一个多输入深度学习框架 (Enhancer-MDLF).
  • 对Enhancer-MDLF与之前的方法 (Enhancer-IF) 进行了对八个人类细胞系的比较分析.
  • 转移学习的应用,以提高增强器的特异性.
  • 使用模型解释技术来识别转录因子结合部位的基因.

主要成果:

  • 与Enhancer-IF相比,Enhancer-MDLF在8个人类细胞系中表现出更高的性能.
  • 该框架在通用增强剂和增强剂-促进剂数据集上表现出强的表现.
关键词:
的 DNA 序列.细胞特异性增强剂 细胞特异性增强剂深度学习是一种深度学习.转移学习转移学习

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Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines
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Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C
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Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C

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Last Updated: Jun 30, 2025

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation
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Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines
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Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

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Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C
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Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C

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  • 转移学习有效地解决了增强特异性预测挑战.
  • 模型解释确定了与增强器区域相关的潜在的转录因子结合位点动图.

    • 结论:

    • 增强器-MDLF为增强器识别提供了一个强大而高性能的解决方案.
    • 该框架对研究增强剂调节机制和基因表达有重大影响.
    • 转移学习和模型解释的整合增强了Enhancer-MDLF在基因组研究中的实用性.