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相关概念视频

Master Transcription Regulators02:23

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
General Transcription Factors01:30

General Transcription Factors

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...
Chromatin Structure and RNA Splicing02:41

Chromatin Structure and RNA Splicing

In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
Master Transcription Regulators02:23

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

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相关实验视频

Updated: Jun 20, 2026

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level
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An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

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MuST:用于单细胞空间转录的多态结构转换

Zelin Zang1,2, Liangyu Li1, Yongjie Xu1

  • 1Westlake Institute for Advanced Studies, Westlake University, HangZhou, 310000, China.

Briefings in bioinformatics
|August 28, 2025
PubMed
概括
此摘要是机器生成的。

空间转录学 (ST) 数据可能会受到主导模式的偏差. 我们开发了多种模式结构转换 (MuST) 来整合多种数据类型, 改善复杂生物系统的组织结构和生物标记分析.

关键词:
生物标志物识别模式偏差多模式整合空间转录学 (ST)拓学的发现

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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科学领域:

  • 基因组学
  • 生物信息学
  • 计算生物学

背景情况:

  • 空间转录学 (ST) 为组织生物学研究提供多模式数据 (转录学,空间,形态).
  • ST数据中的模式偏差来自不一致的模式贡献,有利于分析中占主导地位的模式.
  • 缓解模式偏差对于ST研究的准确下游分析至关重要.

研究的目的:

  • 引入多种模式结构转换 (MuST),一种解决ST数据模式偏差的新方法.
  • 将ST数据中的多式联络信息有效地整合到一个统一的隐藏空间中.
  • 为ST的各种下游分析任务提供坚实的基础.

主要方法:

  • MuST采用拓发现策略和拓融合损失函数.
  • 它学习本质的局部结构以解决不同模式之间的不一致性.
  • 结合基于拓的和深度学习的技术来实现多式联网数据集成.

主要成果:

  • MuST有效地将多模式ST数据集成到一个统一的隐藏空间中.
  • 它在识别和保存组织结构和生物标志物方面优于现有的方法.
  • 在不同模式的精度和协调方面表现出优势.

结论:

  • 使用ST数据分析复杂的生物系统.
  • 该方法成功地减轻了模式偏差,提高了下游任务的性能.
  • 提供先进的ST数据分析的基础,改善生物洞察力.