Computational prediction of proteotypic peptides

Expert Review of Proteomics

Volumn 4, Issue 3, 2007, Pages 351-354

  Blonder, Josip ^a   Veenstra, Timothy D ^a  

^a SAIC FREDERICK INC   (United States)

Author keywords

Computational prediction; Mass spectrometry; Peptide identification; Proteotypic peptide; Quantitative proteomics

Indexed keywords

AMINO ACID; PEPTIDE; PROTEIN;

ANALYTIC METHOD; ORGANISM; PHYSICAL CHEMISTRY; PREDICTION; PROTEIN ANALYSIS; PROTEOMICS; REVIEW;

EID: 34250014360     PISSN: 14789450     EISSN: 17448387     Source Type: Journal    
DOI: 10.1586/14789450.4.3.351     Document Type: Review

References (5)

1. Mallick P, Schirle M, Chen SS et al. Computational prediction of proteotypic peptides for quantitative proteomics. Nat. Biotechnol. 25(1), 125-131 (2007). •• Discussion on the computational approaches used to determine which physicochemical properties are most relevant to proteotypic peptides.
2. Flory MR, Griffin TJ, Martin D, Aebersold R. Advances in quantitative proteomics using stable isotope tags. Trends Biotechnol. 20(12 Suppl.), S23-S29 (2002).
3. Peng J, Elias JE, Thoreen CC, Licklider LJ, Gygi SP. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2(1), 43-50 (2003).
4. Gavin AC, Aloy P, Grandi P et al. Proteome survey reveals modularity of the yeast cell machinery. Nature 440(7084) 631-636 (2006).
5. Petritis K, Kangas LJ, Ferguson RL et al. Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses. Anal. Chem. 75(5) 1039-1048 (2003). • Details the development of a normalized elution time predictor for peptides in proteomic mixtures separated using reverse-phase liquid chromatography.