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相关概念视频

Transcription Factors02:16

Transcription Factors

75.6K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

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Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
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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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Combinatorial Gene Control02:33

Combinatorial Gene Control

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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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相关实验视频

Updated: May 25, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
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Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

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预测TF-目标基因协会使用异质网络和增强负性采样.

Thanh Tuoi Le1,2, Xuan Tho Dang3

  • 1Faculty of Information Technology, Hanoi National University of Education, Hanoi, Vietnam.

Bioinformatics and biology insights
|February 27, 2025
PubMed
概括

这项研究引入了一种用于选择增强负样本的新方法,以改善转录因子 (TF) -目标基因相互作用的预测,这对于理解生物过程和疾病至关重要.

关键词:
异质网络是异质的网络.TF目标基因关联.增强的负样本增强的负样本一个元路径的元路径.

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科学领域:

  • 分子生物学分子生物学
  • 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:

  • 识别转录因子 (TF) -目标基因相互作用对于理解生物机制和疾病至关重要.
  • 用于TF目标基因鉴定的实验方法往往是繁的,昂贵的,范围有限的.
  • 现有的计算方法主要预测TF结合站点,而不是直接相互作用,并与强大的样本数据集构建作斗争.

研究的目的:

  • 提出一种选择增强负样本的新方法,以提高预测TF-目标基因相互作用的准确性.
  • 为了应对由于当前方法的负样本选择不足而导致潜在的TF目标基因关系的不完全覆盖的挑战.

主要方法:

  • 在TF目标基因相互作用数据集中选择增强负样本的新战略的开发.
  • 使用5倍交叉验证验证拟议方法的验证.

主要成果:

  • 拟议的方法实现了0.9024 ± 0.0008.8的曲线下的高平均面积 (AUC).
  • 与现有的方法相比,在预测TF-目标基因相互作用方面显著改善.

结论:

  • 开发的方法通过改善负样本选择,有效地提高了TF目标基因相互作用的预测.
  • 该模型具有很高的效率和准确性,在大规模的生物医学研究和数据分析中具有广泛应用的潜力.