The PeptideAtlas project

By Frank Desiere, Eric W. Deutsch, Nichole L. King, Alexey I. Nesvizhskii, Parag Mallick, Jimmy K. Eng, Sharon Chen, J. Eddes, S. Loevenich, R. Aebersold. Nucleic Acids Res., 2005

812 citations recorded by the source corpus.

The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. PeptideAtlas () addresses these needs by identifying peptides by tandem mass spectrometry (MS/MS), statistically validating those identifications and then mapping identified sequences to the genomes of eukaryotic organisms. A meaningful comparison of data across different experiments generated by different groups using different types of instruments is enabled by the implementation of a uniform analytic process. This uniform statistical validation ensures a consistent and high-quality set of peptide and protein identifications. The raw data from many diverse proteomic experiments are made available in the associated PeptideAtlas repository in several formats. Here we present a summary of our process and details about the Human, Drosophila and Yeast PeptideAtlas builds.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/76a3548d1c50130ac235db73151662c7050c810d

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In Molecular Biology

  1. Matthias Mann
  2. Jüergen Cox
  3. Alexey I. Nesvizhskii
  4. R. Aebersold
  5. David Haussler
  6. UniProt Consortium
  7. Burkhard Rost
  8. Manolis Kellis

In Spectroscopy

  1. Matthias Mann
  2. Jüergen Cox
  3. R. Aebersold
  4. Alexey I. Nesvizhskii
  5. Christoph Schaab
  6. T. Geiger
  7. Eric W. Deutsch
  8. Paola Picotti

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