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Related Concept Videos

Proteomics01:33

Proteomics

10.1K
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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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Related Experiment Video

Updated: Mar 22, 2026

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

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HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Kenneth Bryan1, Mohamed-Ali Jarboui2, Cinzia Raso3

  • 1EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Health and Medical Research Institute , North Terrace, Adelaide, South Australia 5000, Australia.

Journal of Proteome Research
|April 19, 2016
PubMed
Summary
This summary is machine-generated.

HiQuant is a new software tool designed to streamline the analysis of large proteomics datasets. It significantly speeds up complex data processing and interpretation for spatial and temporal proteome dynamics studies.

Keywords:
bioinformaticsdata analysishigh-dimensional datamass spectrometrynetwork analysisprotein quantificationproteomicssoftwarevisualization

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Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Mass-spectrometry-based proteomics generates large, complex datasets.
  • Current computational methods struggle with post-quantification analysis of these large datasets.
  • Efficient analysis is crucial for understanding spatial and temporal proteome dynamics.

Purpose of the Study:

  • To introduce HiQuant, a novel application for post-quantification analysis of large-scale proteomics data.
  • To provide a user-friendly and automated workflow for data processing, quality control, and statistical analysis.
  • To facilitate the interpretation of complex proteomics results through visualization and network analysis.

Main Methods:

  • Developed HiQuant, a software application with a graphical interface and command-line mode.
  • Implemented data processing steps including assay normalization, grouping, and quality control.
  • Integrated interactive heatmap analysis and export to network analysis platforms (Cytoscape, Gephi).

Main Results:

  • HiQuant demonstrated a 200-fold improvement in execution time on a large interactome mapping dataset.
  • Successfully analyzed complex proteome-wide quantification data from various studies.
  • Validated utility in analyzing tyrosine kinase siRNA knockdown and KSR1/KSR2 interactome dynamics.

Conclusions:

  • HiQuant offers a significant advancement in handling and analyzing large-scale proteomics data.
  • The application enhances the efficiency and interpretability of proteomic studies.
  • HiQuant is a valuable tool for researchers investigating proteome dynamics and interactions.