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Updated: Jul 19, 2026

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
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使用空间蛋白质组学来增强细胞类型的分配在组织学图像中的图像

Monica T Dayao1, Aaron T Mayer2, Alexandro E Trevino2

  • 1Joint Carnegie Mellon University-University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, PA 15213, USA; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Cell reports methods
|October 16, 2025
PubMed
概括

这项研究引入了一种机器学习框架,用于改进在组织学图像中的细胞类型识别,使用血素和素 (H&E) 染色. 人工智能模型增强了标准病理学幻灯片中的分子细节,有助于疾病研究.

关键词:
CP:计算生物学 计算机生物学CP: 图像处理 图像处理细胞类型的注释.计算机视觉 计算机视觉深度学习是一种深度学习.基础模型 基础模型组织学 组织学机器学习是机器学习.医学成像医学成像空间蛋白质组学 空间蛋白质组学

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Proteomics01:33

Proteomics

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 proteomics...