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相关概念视频

The Eukaryotic Promoter Region02:40

The Eukaryotic Promoter Region

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Reporter Genes02:11

Reporter Genes

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Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
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Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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Neural Circuits01:25

Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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RNA Polymerase II Accessory Proteins02:36

RNA Polymerase II Accessory Proteins

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Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...
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A Contrastive Learning Framework for Efficient Viral Escape Prediction.

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相关实验视频

Updated: Jul 1, 2025

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions
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Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

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通过图形卷积网络识别促进子和增强子序列.

Samet Tenekeci1, Selma Tekir1

  • 1Department of Computer Engineering, Izmir Institute of Technology, Izmir, 35430, Turkiye.

Computational biology and chemistry
|March 2, 2024
PubMed
概括

这项研究介绍了GCN4EPI,这是一种基于图形的新型模型,用于增强剂-促进剂相互作用的分类. 它通过半监督学习实现了卓越的准确性和更快的训练,大大提高了对遗传调节的理解.

科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 了解遗传调节对于破译细胞功能至关重要.
  • 识别促进剂和增强剂之间的相互作用是理解这一点的关键.
  • 现有的方法在有效和准确地分类这些相互作用方面面临挑战.

研究的目的:

  • 开发一种新的基于图形的半监督学习模型,用于增强剂-促进剂相互作用 (EPI) 的分类.
  • 提高预测增强剂-促进剂关系的准确性和效率.
  • 为了利用序列特征和交互信息来提高预测性能.

主要方法:

  • 开发了一个图形卷积网络 (GCN) 架构,GCN4EPI.
  • DNA序列特征被表示为节点嵌入,EPI信息作为图边.
  • 采用半监督学习来减少数据和培训时间要求.

主要成果:

  • 与基准数据集上的最先进方法相比,GCN4EPI的F1得分高出10%.
  • 该模型展示了高达3倍更快的训练时间.
  • 跨细胞系数据的性能提高了3%的F1得分,表明了稳定性.
关键词:
增强器 增强器 增强器图表卷积网络的图表卷积网络.自然语言处理自然语言处理.活动主办人 活动主办人序列分析是指进行序列分析.

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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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相关实验视频

Last Updated: Jul 1, 2025

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions
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Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

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结论:

  • 将交互信息与序列特征集成,显著提高了EPI分类中的预测性能.
  • GCN4EPI提供了一种更有效,更准确的方法来理解遗传调节.
  • 该模型能够从序列和图形结构中学习,这突显了基因组学中基于图形的学习的力量.