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相关概念视频

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...
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Combinatorial Gene Control02:33

Combinatorial Gene Control

8.4K
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...
8.4K
Operon Model01:23

Operon Model

110
The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...
110
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
994
Inducible Operons: lac Operon01:25

Inducible Operons: lac Operon

129
The lac operon in Escherichia coli is a model for understanding inducible gene regulation and metabolic flexibility. It integrates local control by lactose and global regulation through catabolite repression, enabling E. coli to preferentially metabolize glucose when available and switch to lactose utilization when glucose is scarce.Structure and Function of the lac OperonThe lac operon contains three structural genes: lacZ (β-galactosidase), lacY (lactose permease), and lacA...
129
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

10.1K
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...
10.1K

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相关实验视频

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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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在基因调节网络推断问题中的实际不可分辨性,一个案例研究

Cody E FitzGerald, Shelley Reich, Victor Agaba

    ArXiv
    |September 5, 2025
    PubMed
    概括

    这项研究突出了计算生物学建模的挑战. 我们通过比较数以千计的模型, 发现了线虫发育中的常见调节网络,

    科学领域:

    • 计算生物学
    • 系统生物学
    • 发育生物学

    背景情况:

    • 生物数据分析面临着噪音,有限的测量和未观察到的状态.
    • 模型开发带来不确定性,导致多个竞争结构.
    • 在数学生物学中,模型的选择和结构的比较是未充分利用的.

    研究的目的:

    • 解决在生物建模中分析结构不确定性的需要.
    • 使用强大的建模框架从生物数据中推断机械洞察力.
    • 通过实验数据确定关键的监管特征和网络结构.

    主要方法:

    • 进行了数学生物学出版物的元分析,以评估建模实践.
    • 开发和比较了13,824种不同的线虫发展监管网络模型.
    • 在三个实验条件中利用真实生物数据进行模型评估.

    主要成果:

    • 在实验条件下确定了一套常见的监管特征.
    • 发现了适用于各种条件的保守监管网络结构.
    • 最适合的模型显示了关键监管机构 (eud-1, sult-1, nhr-40) 的高正规性和相互连接性.

    结论:

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    • 开发的建模框架有效地从生物数据中推断出监管网络结构.
    • 已识别的调节网络提供了关于线虫发育的机制性见解.
    • 挑战和框架广泛适用于需要复杂数据分析的各种科学领域.