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相关概念视频

Proteomics01:33

Proteomics

7.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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相关实验视频

Updated: Jun 13, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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亲近图 - 一个基于网络的多omics框架,以捕捉组织异质性,整合单细胞omics和空间分析.

Santhoshi N Krishnan1, Sunjong Ji2, Ahmed M Elhossiny1

  • 1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Computers in biology and medicine
|September 10, 2024
PubMed
概括

我们开发了Proximogram,这是一个新的图形表示,集成了omics和空间数据. 这种方法通过捕捉细胞相互作用和空间结构来增强疾病分类,有助于识别诊断标记物.

关键词:
图形卷积网络:GCN 卷积网络图形理论是指图形的理论.俄米克斯 (Omics) 是一个电子游戏.胰腺癌是一种胰腺癌.空间分析是一种空间分析.

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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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相关实验视频

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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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科学领域:

  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.
  • 系统生物学 系统生物学

背景情况:

  • 越来越多的患者衍生多式生物数据可用.
  • 整合不同的数据类型 (omics,空间) 对于疾病理解至关重要.
  • 目前的方法可能无法最佳地利用组合的生物数据.

研究的目的:

  • 提出Proximogram,一种新的基于图形的表示,用于联合嵌入omics和空间数据.
  • 为了评估Proximogram在疾病分类中的有效性.
  • 为了确定驱动疾病分类的关键生物特征.

主要方法:

  • 从多重免疫光图像和单细胞RNA-seq数据生成的近距离图.
  • 利用了胰腺正常,慢性胰腺炎 (CP) 和胰腺管腺癌 (PDAC) 患者的数据.
  • 应用图形深度学习模型使用近距离图作为输入.

主要成果:

  • 亲近图集成了来自单细胞信号和空间细胞架构的结构信息.
  • 使用近距离图的图形深度学习模型显示,与更简单的空间图表相比,分类性能有所改善.
  • 增强的歧视力凸显了综合数据的价值.

结论:

  • 普罗克西姆图提供了一种强大的方法,用于共同分析多式联络生物数据.
  • 通过Proximogram整合空间和omics数据可以提高疾病分类的准确性.
  • 这种方法可以识别胰腺疾病的重要诊断标志物.