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相关概念视频

Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...

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Updated: Jun 29, 2026

Transcriptome Analysis of Single Cells
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推断模式驱动单细胞和空间转录组的细胞间流动.

Axel A Almet1,2, Yuan-Chen Tsai3,4,5, Momoko Watanabe3,4,5

  • 1Department of Mathematics, University of California, Irvine, Irvine, CA, USA.

Nature methods
|August 26, 2024
PubMed
概括
此摘要是机器生成的。

FlowSig从基因表达数据中推断出细胞间通信流. 这种方法揭示了细胞信号如何驱动基因模块活动,并揭示了复杂的生物信号模式.

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科学领域:

  • 基因组学就是基因组学.
  • 系统生物学 系统生物学
  • 计算生物学 计算生物学

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 和空间转录组学 (ST) 提供了高维基基因表达数据.
  • 基因表达模式通常由细胞间通信网络或基因模块描述,通常假定它们独立运行.
  • 现有的方法缺乏描述细胞内基因模块介导的定向细胞间信息流的能力.

研究的目的:

  • 介绍FlowSig,一种用于从scRNA-seq或ST数据中推断通信驱动的细胞间流动的新方法.
  • 为了解决描述细胞间信号传递动态的方法学的差距.
  • 分析细胞间通信如何影响细胞内基因模块活动.

主要方法:

  • FlowSig使用图形因果建模和条件独立来推断细胞间流动.
  • 该方法使用实验性皮质有机体数据和数学建模的合成数据进行基准测试.
  • 适用于各种生物系统,以证明其能力.

主要成果:

  • FlowSig成功地从转录基因数据中推断出通信驱动的细胞间流.
  • 基准测试证实了该方法在实验和合成数据集上的准确性.
  • 该方法捕捉了胰腺小岛中刺激诱导的膜信号变化.
  • FlowSig识别了与COVID-19严重程度相关的细胞间流动的变化.
  • 在小鼠胚胎发生过程中实现了形态原驱动的激活剂-抑制剂模式的重建.

结论:

  • FlowSig提供了一个强大的框架,用于从基因表达数据中剖析细胞间通信动态.
  • 该方法揭示了细胞间信号和细胞内基因模块之间的相互作用.
  • 在理解各种生物过程方面,FlowSig具有广泛的应用性,从发育到疾病.