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Proteomics

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...

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Related Experiment Video

Updated: Jun 13, 2025

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Published on: November 17, 2019

Graphical and Interactive Spatial Proteomics Image Analysis Workflow.

Pritpal Singh¹, Jocelyn H Wright¹, Kimberly S Smythe¹

¹School of Engineering and Technology, University of Washington Tacoma, WA.

Biorxiv : the Preprint Server for Biology

|June 12, 2025

Summary

This summary is machine-generated.

We developed a flexible, high-throughput spatial proteomics imaging workflow for biomedical researchers. This tool enables reproducible analysis and visualization of protein expression in cells and tissues.

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Area of Science:

Biomedical research
Proteomics
Computational biology

Background:

Spatial proteomics offers detailed protein expression and localization data within cells and tissues.
Existing imaging workflows lack flexibility, high-throughput capabilities, and interactive visualization for spatial proteomic analysis.

Purpose of the Study:

To present a modular, interactive, and containerized spatial proteomics imaging workflow.
To empower biomedical researchers with reproducible and customizable complex analysis tools.

Main Methods:

The workflow includes cell segmentation, unsupervised clustering, cluster validation, and visualization.
A form-based graphical interface allows single-click execution, interactive adjustments, and parameter modification.
The workflow was tested on a high-plex immunohistochemistry-stained cancer tissue microarray (TMA).

Main Results:

The workflow successfully processed a cancer imaging dataset with diverse cell types.
Demonstrated applicability to various biopsy types and reproducible execution of complex analyses.
Enabled interactive customization of image processing and analysis steps.

Conclusions:

The developed spatial proteomics imaging workflow is flexible, high-throughput, and user-friendly.
It facilitates reproducible and customizable analysis of spatial proteomic data for biomedical research.
The workflow supports interactive visualization and broad applicability across different tissue types.