An Automated method for the analysis of stable isotope labeling data in proteomics

Xiang Zhang, Wade Hines, Jiri Adamec, John M. Asara, Stephen Naylor, Fred E. Regnier

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


An algorithm is presented for the generation of a reliable peptide component peak table from liquid chromatography-mass spectrometry (LC-MS) and subsequent quantitative analysis of stable isotope coded peptide samples. The method uses chemical noise filtering, charge state fitting, and deisotoping toward improved analysis of complex peptide samples. Overlapping peptide signals in mass spectra were deconvoluted by correlation with modeled peptide isotopic peak profiles. Isotopic peak profiles for peptides were generated in silico from a protein database producing reference model distributions. Doublets of heavy and light labeled peak clusters were identified and compared to provide differential quantification of pairs of stable isotope coded peptides. Algorithms were evaluated using peptides from digests of a single protein and a seven-protein mixture that had been differentially coded with stable isotope labeling agents and mixed in known ratios. The experimental results correlated well with known mixing ratios.

Original languageEnglish (US)
Pages (from-to)1181-1191
Number of pages11
JournalJournal of the American Society for Mass Spectrometry
Issue number7
StatePublished - Jul 2005
Externally publishedYes

ASJC Scopus subject areas

  • Structural Biology
  • Spectroscopy


Dive into the research topics of 'An Automated method for the analysis of stable isotope labeling data in proteomics'. Together they form a unique fingerprint.

Cite this