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相关概念视频

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

10.0K
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...
10.0K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

6.5K
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...
6.5K
Next-generation Sequencing03:00

Next-generation Sequencing

91.6K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
91.6K

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相关实验视频

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DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
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DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

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ChromDL:一个下一代监管DNA分类器.

Christopher Hill1,2, Sanjarbek Hudaiberdiev1, Ivan Ovcharenko1

  • 1Computational Biology Branch, Intramural Research Program, National Library of Medicine, National Institutes of Health, Bethesda, MD 20892, United States.

Bioinformatics (Oxford, England)
|June 30, 2023
PubMed
概括

ChromDL是一种新型深度学习模型,通过分析DNA序列,准确地预测基因调节元素. 基因组学的这一进步有助于理解转录因子结合和基因特征.

科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 机器学习 机器学习

背景情况:

  • 仅从序列数据中预测非编码DNA的调节功能在基因组学中是一个重大挑战.
  • 优化算法,GPU速度和机器学习库的进步使复杂的神经网络架构的开发成为可能.

研究的目的:

  • 开发一种深度学习模型,准确预测非编码DNA中的调控元素.
  • 改进现有的方法,预测转录因子结合部位,基因组修饰和DNase-I过敏部位.

主要方法:

  • 进行了成千上万种深度学习架构的比较分析.
  • 开发了ChromDL,集成双向封闭循环单元,卷积神经网络和双向长期短期记忆单元.
  • 对于基因调控元件的分类,采用了二级模型.

主要成果:

  • 与以前的模型相比,ChromDL显著提高了转录因子结合部位,基因组修饰和DNase-I过敏部位的预测指标.
  • 该模型证明了对弱转录因子结合的改进检测.
  • 克罗姆DL促进了基因调节元件的准确分类,并有助于划分转录因子结合基因特异性.

结论:

  • 克罗姆DL在预测非编码DNA的调节功能方面取得了重大进展.

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相关实验视频

Last Updated: Jul 25, 2025

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq
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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

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Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants

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  • 该模型检测弱转录因子结合和分类调控元素的能力对未来的基因组研究具有潜力.
  • ChromDL的源代码是公开的,促进了进一步的研究和开发.