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Related Concept Videos

Proteomics01:33

Proteomics

10.3K
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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Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

Joseph Slagel1, Luis Mendoza1, David Shteynberg1

  • 1From the ‡Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109.

Molecular & Cellular Proteomics : MCP
|November 25, 2014
PubMed
Summary

Cloud computing accelerates proteomics research by offering scalable, affordable data analysis. The Trans-Proteomic Pipeline now integrates cloud functionality, enabling faster processing of mass spectrometry data for all researchers.

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Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Mass spectrometry-based proteomics generates large datasets requiring significant computational resources.
  • Access to scalable and affordable computing infrastructure is crucial for advancing proteomics research.
  • Existing tools may not adequately address the computational demands of large-scale proteomics studies.

Purpose of the Study:

  • To introduce cloud computing capabilities into the Trans-Proteomic Pipeline (TPP) for mass spectrometry data analysis.
  • To enable researchers to leverage scalable cloud resources for proteomics data processing.
  • To provide a cost-effective and accessible solution for large-scale proteomics studies.

Main Methods:

  • Integration of Amazon Web Services (AWS) cloud computing with the Trans-Proteomic Pipeline.
  • Deployment of TPP in a fully hosted AWS environment for data and software residency.
  • Option to run computationally intensive tasks on Amazon Elastic Compute Cloud (EC2) instances from a local computer.
  • Development of tutorials for rapid deployment of cloud-enabled TPP.

Main Results:

  • TPP now provides access to large-scale computing resources on AWS for all users.
  • Cloud-enabled TPP significantly reduces analysis times for tandem mass spectrometry datasets.
  • Performance and cost analyses of various EC2 instance types were conducted.
  • Demonstrated successful processing of over 1100 mass spectrometry files through four search engines in 9 hours at low cost.

Conclusions:

  • Cloud computing integration enhances the TPP, making advanced proteomics data analysis more accessible and efficient.
  • The developed cloud service offers a scalable, affordable, and user-friendly solution for mass spectrometry-based proteomics.
  • Researchers can rapidly adopt cloud technology for their proteomics workflows using the provided tools and tutorials.