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Related Concept Videos

Proteomics01:33

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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

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

Published on: August 19, 2025

Methods, algorithms and tools in computational proteomics: a practical point of view.

Rune Matthiesen1

  • 1Bioinformatics Group, CIC bioGUNE, CIBER-HEPAD, Technology Park of Bizkaia, Derio, Bizkaia, Spain. ruma@cicbiogune.es

Proteomics
|August 19, 2007
PubMed
Summary

Computational proteomics, crucial for high-throughput analysis, requires more attention. This review covers essential computational tools for mass spectrometry (MS)-based proteomics data analysis, including peptide and protein identification.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput analysis in large-scale experimental proteomics projects drives the need for computational tools.
  • Mass spectrometry (MS)-based proteomics generates complex data requiring sophisticated analysis methods.
  • Current computational resources for proteomics lag behind those for other fields like microarrays.

Purpose of the Study:

  • To provide a comprehensive overview of computational tools for MS-based proteomics data analysis.
  • To discuss algorithms and methods for key proteomics tasks such as peptide/protein identification and quantification.
  • To stimulate further research and development in the field of computational proteomics.

Main Methods:

  • Literature review of existing computational tools and algorithms for MS-based proteomics.
  • Discussion of methods for peptide and protein identification from MS data.
  • Exploration of techniques for quantitative proteomics and data storage.

Main Results:

  • Identified a range of computational tools for analyzing MS-based proteomics data.
  • Detailed algorithms and methods for peptide/protein identification and quantitative proteomics.
  • Highlighted the complexity of proteomics data analysis compared to microarray analysis.

Conclusions:

  • Computational proteomics is an emerging field with significant demand for advanced tools.
  • Further scientific attention and development are needed to address the complexity of proteomics data analysis.
  • The review aims to foster discussion and advance the field of computational proteomics.