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相关概念视频

Types of Selection01:46

Types of Selection

45.2K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

16.6K
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
16.6K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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No description available
5.6K
T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

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T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...
16.1K
T Cell Types and Functions01:24

T Cell Types and Functions

2.5K
When T cells with CD4 markers are activated, they give rise to two types of effector cells: helper T cells and regulatory T cells. Meanwhile, T cells with CD8 markers differentiate into effector cytotoxic T cells. The differentiation of CD4 T cells into helper T cell subsets, such as Th1, Th2, and Th17 cells, is dependent on the antigen type, antigen-presenting cell, and regulatory cytokines.
Th1 cells stimulate dendritic cells to express necessary co-stimulatory molecules on their surfaces for...
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Connective Tissue Cell Types01:22

Connective Tissue Cell Types

4.2K
Connective tissue develops from the mesoderm of a developing embryo and consists of cells, fibers, and ground substance: a gel-like material containing large complexes of carbohydrates and proteins. Connective tissue was first identified as a separate tissue family in the 18th century, and Johannes Peter Muller coined the term connective tissue.
Fat cells (adipocytes), smooth muscle cells (myoblasts), and bone cells (osteoblasts) are some connective tissue cell types. Some immune system cells...
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相关实验视频

Updated: Feb 5, 2026

Isolation and Transcriptome Analysis of Plant Cell Types
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通过Festem直接选择细胞类型标记基因进行单细胞聚类分析的协议.

Zihao Chen1, Changhu Wang1, Ruibin Xi1

  • 1School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing 100871, China.

STAR protocols
|December 19, 2024
PubMed
概括

通过期望最大化测试 (Festem) 进行特征选择,直接识别单细胞RNA测序 (scRNA-seq) 数据的细胞类型标记基因. 该协议通过提供聚类和标记基因识别来增强生物解释.

科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 产生高维数据,需要强大的特征选择.
  • 识别细胞类型特定的标记基因对于解释scRNA-seq数据和理解细胞异质性至关重要.
  • 现有的方法可能无法直接促进下游聚类的标记基因选择.

研究的目的:

  • 为scRNA-seq数据分析提供使用特征选择通过预期最大化测试 (Festem) 的详细协议.
  • 为了证明Festem如何实现细胞类型标记基因的直接选择.
  • 为了促进后续的聚类和标记基因分配,以提高生物解释.

主要方法:

  • 实现Festem算法用于特征选择.
  • 关于Festem环境设置的逐步指南.
  • 标记基因选择,数据聚类和标记基因分配的详细程序.

主要成果:

  • 使用Festem.成功识别了细胞类型标记基因.
  • 从scRNA-seq数据生成可靠的聚类结果.
  • 综合输出提供聚类和标记基因的综合分析.
关键词:
在RNA-seqqq.生物信息学是一种生物信息学.一个单细胞的单细胞.系统生物学 系统生物学

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Reusable Single Cell for Iterative Epigenomic Analyses
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Reusable Single Cell for Iterative Epigenomic Analyses

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Flow Cytometry Protocols for Surface and Intracellular Antigen Analyses of Neural Cell Types

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相关实验视频

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Flow Cytometry Protocols for Surface and Intracellular Antigen Analyses of Neural Cell Types

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结论:

  • 费斯特姆协议为scRNA-seq数据中的标记基因选择提供了直接和有效的方法.
  • 这种方法提高了从scRNA-seq实验中获得的生物信息的解释性.
  • 该协议为研究人员分析单细胞基因表达数据提供了宝贵的工具.