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相关概念视频

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Combinatorial Gene Control

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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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General Transcription Factors01:30

General Transcription Factors

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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...
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相关实验视频

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Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells
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从单细胞数据推断细胞类型特定的共同表达基因.

Xinning Shan, Hongyu Zhao

    bioRxiv : the preprint server for biology
    |November 28, 2024
    PubMed
    概括

    控制错误阳性对于从单细胞数据中准确推断基因共同表达网络至关重要. 一种新的基于模拟的p值方法为评估方法性能提供了可靠的方法.

    科学领域:

    • 基因组学就是基因组学.
    • 计算生物学 计算生物学
    • 一个单细胞分析.

    背景情况:

    • 细胞类型特定的基因共同表达网络对于理解基因关系至关重要.
    • 目前用于从单细胞数据中推断这些网络的方法往往缺乏强大的假阳性控制.
    • 不充分的假阳性对照可以导致对方法性能产生误导性结论,即使具有高可重现性或功能连贯性.

    研究的目的:

    • 开发一种高效的模拟工具来推导经验p值,以控制共同表达推理中的假阳性.
    • 用模拟和真实单细胞数据来评估基于p值的方法的性能,以推断细胞类型特定的共同表达.
    • 解决方法评估中的偏差,包括已知的生物网络中的随机重叠和表达水平偏差.

    主要方法:

    • 开发一个模拟工具来生成经验p值的基因共表达推断.
    • 基于p值的方法的评估,使用模拟和真实单细胞数据集.
    • 分析网络比较中的潜在偏差,例如随机重叠和表达级别效应.

    主要成果:

    • 该模拟工具有效地推导出经验p值,以控制共同表达推理中的假阳性.
    • 基于p值的方法证明了推断细胞类型特定的共同表达的力量.
    • 确定并说明偏差的影响,包括随机重叠和表达水平偏差,对方法评估.

    更多相关视频

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    A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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    结论:

    • 控制错误阳性对于可靠的基因共同表达网络推断至关重要.
    • 拟议的基于模拟的p值方法为评估共表达推理工具提供了一个强大的策略.
    • 这种方法提高了从单细胞数据分析中得出的结果的准确性和可靠性.