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Proteomics

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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...

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Updated: Jun 4, 2026

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

Database resources for proteomics-based analysis of cancer.

Guang Lan Zhang¹, David S DeLuca, Vladimir Brusic

¹Cancer Vaccine Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.

Methods in Molecular Biology (Clifton, N.J.)

|March 4, 2011

Summary

This review highlights essential bioinformatics databases for cancer proteomics research. These resources aid in analyzing gene expression, mutations, and protein interactions for better cancer studies.

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Last Updated: Jun 4, 2026

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

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Published on: February 27, 2015

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

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Area of Science:

Proteomics
Bioinformatics
Cancer Research

Background:

Biological and bioinformatics databases are crucial for organizing and accessing diverse biological information.
These databases facilitate medical and biological research by providing structured data access.

Purpose of the Study:

To review publicly available databases relevant to proteomics studies in cancer research.
To identify key resources for gene/protein expression, mutations, and interactions.

Main Methods:

Literature review of publicly available bioinformatics databases.
Categorization of databases based on their relevance to cancer proteomics (e.g., expression, mutation, interaction, pathway).

Main Results:

Identified key databases for gene/protein expression, gene mutation, single nucleotide polymorphisms (SNPs), tumor antigens, protein-protein interactions (PPIs), and biological pathways.
Highlighted the utility of automated information retrieval for large-scale proteomics data analysis.

Conclusions:

Publicly available bioinformatics databases are indispensable tools for cancer proteomics research.
Leveraging these diverse databases enables efficient and comprehensive analysis of complex proteomics data in cancer.