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相关概念视频

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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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...
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.0K
Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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相关实验视频

Updated: Jul 1, 2025

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

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从局部到全球基因共同表达估计使用单细胞RNA-seq数据.

Jinjin Tian1, Jing Lei1, Kathryn Roeder1

  • 1Department of Statistics and Data Science, Carnegie Mellon University, 15213, Pittsburgh, PA, United States.

Biometrics
|March 11, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了平均局部密度差距 (aLDG),这是一种分析基因学中复杂基因关系的新方法. aLDG有效地捕捉了局部和非线性依赖,在各种生物应用中表现优于现有的措施.

关键词:
测量依赖度的措施.基因的共同表达.独立性测试测试的测试方法一个单细胞RNA-seqq.空间和时间数据.

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

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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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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科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 统计遗传学 统计遗传学

背景情况:

  • 基因关系对于生物学见解至关重要,但通常是局部的,非线性的,并且很难用大数据集来建模.
  • 现有的依赖性测量与局部基因关系扎,或是计算密集.
  • 细胞特异性基因网络提供了一种有前途的方法,以在颗粒级特征基因相互作用.

研究的目的:

  • 为分析局部基因关系开发一种新,强大,计算效率高的依赖度量.
  • 引入平均局部密度差距 (aLDG) 和其小型批量变体,用于表征基因相互作用.
  • 证明aLDG在各种基因组学应用中的实用性,包括基因关系估计和轨迹分析.

主要方法:

  • 开发了细胞特异性基因网络,以在单细胞水平上建模基因关系.
  • 通过平均细胞特异关系引入平均局部密度差距 (aLDG).
  • 使用了一致的非参数估计器来确定稳定性,并探索了结构化数据的迷你批量平均值.
  • 应用aLDG对对基因关系估计,细胞轨迹分叉检测和空间转录学可视化.

主要成果:

  • 平均局部密度差距 (aLDG) 能够有效地检测非线性和非单调的基因关系.
  • aLDG在人口和经验层面上都表现出了稳健性.
  • 通过对小批量进行平均化,突出显示了局部结构的变化,改善了对空间或时间结构数据的分析.
  • aLDG及其变体在模拟和现实世界基因组数据分析中优于现有方法.

结论:

  • aLDG为了解基因组学中复杂的局部基因依赖提供了一个强大的新工具.
  • aLDG的小批量变体增强了结构化生物数据的分析,例如空间转录学.
  • 这种方法比基因关系推断和生物发现的现有方法具有显著的优势.