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相关概念视频

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...
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Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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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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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
149
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

1.0K
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...
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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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相关实验视频

Updated: Sep 11, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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基于对比学习的基因监管网络推理的多omics数据集成框架.

Yongqing Zhang, Zhigan Zhou, Maocheng Wang

    IEEE transactions on computational biology and bioinformatics
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    PubMed
    概括
    此摘要是机器生成的。

    我们开发了CLMOGRI,这是一个新的框架,用于从多omics数据中推断基因调节网络 (GRNs). 该工具有效地整合了各种生物数据,以确定关键的监管要素并提高网络的可解释性.

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    相关实验视频

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    科学领域:

    • 计算生物学 计算生物学
    • 系统生物学 系统生物学
    • 生物信息学是一种生物信息学.

    背景情况:

    • 基因调控网络 (GRNs) 对于在分化过程中保持细胞稳定性和功能至关重要.
    • 现有的方法很难有效地整合多omics数据用于细胞类型特定的GRN推断.

    研究的目的:

    • 引入CLMOGRI,这是一个新的多omics框架,用于推断转录因子-基因调控网络.
    • 增强多种omics数据的集成,以实现更准确的GRN构建.

    主要方法:

    • CLMOGRI利用异质网络和对比学习将多omics数据嵌入到统一的功能空间中.
    • 随机步行技术用于特征提取和节点相似性测量.
    • 对比学习用于预测基因调节关系.

    主要成果:

    • 在精度回忆曲线下的区域 (AUPR) 和F-Score.中,CLMOGRI显著优于现有的基线方法.
    • 该框架有效地捕获了多omics信息,以进行强大的GRN推断.
    • 在GRN中,CLMOGRI成功地识别了关键节点和模块,提高了可解释性.

    结论:

    • CLMOGRI提供了一个强大的和可解释的方法,用于多omics GRN推断.
    • 该框架提高了我们对复杂的生物相互作用和细胞调节的理解.
    • 在生物系统分析中,CLMOGRI促进了GRNs的实用性.