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相关概念视频

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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Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

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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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Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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Epigenetic Regulation01:37

Epigenetic Regulation

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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
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Epigenetic Regulation01:46

Epigenetic Regulation

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Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
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相关实验视频

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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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通过积极学习优化调控DNA.

Yuxin Shen1, Grzegorz Kudla2, Diego A Oyarzún1,3

  • 1School of Biological Sciences, University of Edinburgh, Edinburgh, UK.

Computational and structural biotechnology journal
|October 27, 2025
PubMed
概括

积极学习通过代优化蛋白质表达来增强生物技术的DNA序列设计. 这种机器学习方法在复杂的生物环境中优于传统方法,提高了工程微生物菌株的产量.

科学领域:

  • 生物技术是生物技术.
  • 合成生物学 合成生物学
  • 机器学习 机器学习

背景情况:

  • 生物技术应用需要为高异质蛋白表达而设计的微生物菌株.
  • 优化调节性DNA元素对于提高蛋白质产量至关重要.
  • 机器学习 (ML) 与高通量实验相结合,有助于找到改进的调节序列.

研究的目的:

  • 探索积极学习 (AL) 作为优化DNA序列以提高蛋白质表达水平的策略.
  • 评估AL循环在复杂的基因型-表型景观中的性能和融合.

主要方法:

  • 测量的代周期,ML模型训练和序列采样/选择.
  • 利用合成数据和经过实验验证的酵母促进剂序列景观.
  • 将AL与一次性优化方法进行比较.

主要成果:

  • 积极学习在复杂的,富有经验的景观中,与一次性优化相比,表现出更高的性能.
  • 在不同的实验条件下,AL有效地优化了序列.
  • 该框架显示了数据集成在各种环境 (实验室,菌株,条件) 中的潜力.

结论:

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  • 积极学习为生物技术中的DNA序列设计和表型优化提供了有效的框架.
  • 在工程微生物系统中,AL为最大限度地提高蛋白质产量提供了一个强大的策略.