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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 proteomics...

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Related Experiment Video

Updated: Jul 3, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Challenges and solutions in proteomics.

Huang Hongzhan¹, Hem D Shukla, Wu Cathy

¹Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington DC, USA.

Current Genomics

|July 23, 2008

Summary

This summary is machine-generated.

We developed iProXpress, an integrated system for analyzing large-scale proteomics data. This tool aids in protein identification and functional interpretation, supporting disease diagnosis and drug development.

Keywords:

Proteomic profiling bioinformatic tools biomarkers high-throughput analysis iProXpress pathway discovery sequence library stage specific proteins

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Area of Science:

Proteomics
Bioinformatics
Systems Biology

Background:

The rapid expansion of proteomics data offers significant opportunities but also presents analytical challenges.
High-throughput proteomic profiling aids in identifying proteins, biomarkers, and therapeutic targets for various diseases, including cancer.
Existing bioinformatics tools have advanced proteomic data analysis, yet gaps remain in fully leveraging large-scale datasets.

Purpose of the Study:

To develop an integrated system, iProXpress, for enhanced analysis of large-scale proteomics data.
To facilitate functional and pathway discovery from complex proteomic datasets.
To support hypothesis generation and knowledge discovery in genomic-scale studies.

Main Methods:

Development of an integrated proteomic expression analysis system, iProXpress.
Utilizing a comprehensive sequence library for protein identification.
Employing integrated data for functional interpretation and pathway analysis.
Modular design for integration with existing proteomic data analysis pipelines.

Main Results:

iProXpress facilitates robust protein identification and functional interpretation.
The system supports the interrogation of multiple data sources for comprehensive analysis.
Enables hypothesis generation and knowledge discovery from large-scale genomic and proteomic studies.

Conclusions:

iProXpress addresses existing gaps in proteomic data analysis, enhancing functional and pathway discovery.
The integrated system aids in disease diagnosis and the development of novel therapeutics.
Facilitates a novel approach to complex biological questions through multi-source data interrogation.