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Related Concept Videos

Proteomics01:33

Proteomics

10.2K
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...
10.2K

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Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

Hannes L Röst1, George Rosenberger1, Ruedi Aebersold2

  • 1ETH Zurich, Institute of Molecular Systems Biology, CH-8093 Zurich, Switzerland and Ph.D. Program in Systems Biology, University of Zurich and ETH Zurich, CH-8057 Zurich, Switzerland.

Bioinformatics (Oxford, England)
|March 20, 2015
PubMed
Summary
This summary is machine-generated.

Researchers can now visualize targeted proteomics data with TAPIR, a new open-source Python software. It supports standardized formats like mzML and TraML for high-throughput proteome-wide studies.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Targeted mass spectrometry is crucial for accurate protein quantification in complex biological samples.
  • Existing software solutions often lack cross-platform compatibility and open-source accessibility.
  • Standardized data exchange formats are essential for maximizing the utility of mass spectrometry techniques.

Purpose of the Study:

  • To develop a fast, efficient, and open-source software for visualizing targeted proteomics data.
  • To enable visualization of chromatograms and peaks from targeted mass spectrometry experiments.
  • To provide a scalable solution for high-throughput proteome-wide studies.

Main Methods:

  • Developed TAPIR, a Python-based visualization software.
  • Utilized open, standardized data formats: mzML for raw data and TraML for experimental context.
  • Ensured cross-platform compatibility and integration with existing analysis pipelines.

Main Results:

  • TAPIR provides fast and efficient visualization of targeted proteomics data.
  • The software supports proteome-wide studies, including those generated by SWATH-MS.
  • TAPIR is scalable and integrates seamlessly with automated analysis workflows.

Conclusions:

  • TAPIR offers a valuable open-source tool for the targeted proteomics community.
  • The software facilitates the analysis of complex, high-throughput mass spectrometry data.
  • TAPIR's framework is extensible for future applications beyond targeted proteomics.