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相关概念视频

Transcription Factors02:16

Transcription Factors

82.8K
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...
82.8K
Transcription Elongation Factors02:35

Transcription Elongation Factors

14.0K
Transcription elongation is a dynamic process that alters depending upon the sequence heterogeneity of the DNA being transcribed. Hence, it is not surprising that the elongation complex's composition also varies along the way while transcribing a gene.
The transcription elongation is regulated via pausing of RNA polymerase on several occasions during transcription. In bacteria, these halts are necessary because the transcription of DNA into mRNA is coupled to the translation of that mRNA...
14.0K
Transcription Elongation Factors02:35

Transcription Elongation Factors

4.8K
4.8K
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

11.9K
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...
11.9K
General Transcription Factors01:30

General Transcription Factors

7.1K
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...
7.1K
Master Transcription Regulators02:23

Master Transcription Regulators

7.8K
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...
7.8K

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相关实验视频

Updated: Feb 7, 2026

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow
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Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

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通过数据平衡和表示学习增强转录因子监管网络分析.

Xuan Tho Dang1

  • 1Academy of Policy and Development, Hanoi, Hanoi, 100000, VIET NAM.

Biomedical physics & engineering express
|February 5, 2026
PubMed
概括

这项研究引入了一种新的计算方法,可以准确预测转录因子 (TF) 和目标基因相互作用,克服数据不平衡问题,以改善癌症研究和药物发现.

科学领域:

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

背景情况:

  • 转录因子 (TF) 和基因相互作用对基因调节至关重要,并与癌症等疾病有关.
  • 用于TF目标预测的实验方法昂贵,缺乏可扩展性.
  • 机器学习模型中的数据不平衡阻碍了TF-target相互作用的准确预测.

研究的目的:

  • 开发一种新的计算框架,用于更好地预测转录因子-向基因相互作用.
  • 为了应对TF-target预测模型中数据不平衡的挑战.
  • 提高生物医学应用TF-目标相互作用预测的准确性和通用性.

主要方法:

  • 整合K-means++集群与数据平衡策略,以减轻偏向低频TF的偏差.
  • 应用深度学习技术,包括随机步行采样和跳过图形嵌入,用于生物网络表示.
  • 使用五重交叉验证方法来评估模型性能.

主要成果:

  • 拟议的方法显著提高了TF-目标相互作用预测的准确性.
  • 实现了0.9452 ± 0.0047.7的曲线下面面积 (AUC) 的平均优势.
  • 通过有效地解决数据不平衡,证明了改进的模型通用化.
关键词:
K-意味着K的意思是K.K-意味着++++的意思.TF的监管相互作用数据失衡处理 处理数据失衡不同质的生物网络.一个元路径的元路径.

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相关实验视频

Last Updated: Feb 7, 2026

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow
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Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

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结论:

  • 这种新型框架为准确的TF-target交互预测提供了强大的解决方案,克服了数据不平衡的挑战.
  • 这种方法对推进分子生物学和生物医学研究具有重大意义.
  • 促进TF目标基因的发现,并有助于开发新的治疗策略.