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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...

Subcellular Fractionation

Subcellular Fractionation

The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
Differential Centrifugation
Differential centrifugation is...

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Related Experiment Video

Updated: Aug 3, 2025

Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier

Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier

Published on: December 9, 2022

Computational Methods for Single-Cell Proteomics.

Sophia M Guldberg^1,2,3, Trine Line Hauge Okholm^1,3,4, Elizabeth E McCarthy^1,2,5

¹Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA;

Annual Review of Biomedical Data Science

|April 11, 2023

Summary

This summary is machine-generated.

Single-cell proteomics generates complex data, requiring advanced computational tools for analysis. This review details single-cell and spatial proteomics pipelines, aiding biological and disease research.

Keywords:

clustering computational methods data analysis mass cytometry spatial proteomics trajectory inference

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Area of Science:

Biotechnology
Computational Biology
Proteomics

Background:

Single-cell proteomics technologies yield high-dimensional datasets with millions of cells.
These datasets offer potential for significant biological and disease-related discoveries.
The complexity necessitates sophisticated computational tools for data processing and visualization.

Purpose of the Study:

To review single-cell and spatial proteomics analysis pipelines.
To describe available computational methods and their performance.
To highlight benchmarking studies on current computational toolkits.

Main Methods:

Literature review of single-cell and spatial proteomics analysis.
Description of computational tools and workflows.
Summary of benchmarking studies on existing software.

Main Results:

Identification of key steps in single-cell and spatial proteomics analysis.
Overview of advantages and limitations of current computational tools.
Emphasis on the need for robust analysis pipelines.

Conclusions:

Advancements in single-cell proteomics require parallel development of robust computational tools.
Effective analysis pipelines are crucial for unlocking the full potential of single-cell proteomic data.
Further development of computational methods will enhance biological and disease insights.