Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome.

By Junmin Peng, Joshua E. Elias, C. Thoreen, L. Licklider, Steven P. Gygi. Journal of Proteome Research, 2003

1,575 citations recorded by the source corpus.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/b6befcbd40dfdf3341ce5dd9e805f1b2a177cde4

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Citations in the corpus

Target-Decoy Search Strategy for Mass Spectrometry-Based Proteomics (2010, methodology): “Proteins— Protein reversal is by far the simplest and most widely used method for creating decoy sequences (see Note 2 for a simple Perl script to create a concatenated target-decoy sequence list based on an input target sequence list) (17,18).”
Decision Tree-Driven Tandem Mass Spectrometry for Shotgun Proteomics (2008, background): “Multidimensional chromatography can parse the peptides temporally over hours, or even days, so that downstream tandem mass spectrometry (MS/MS) instruments can autonomously interrogate as many peptides as possibl”
Quantitative proteomics reveals the function of unconventional ubiquitin chains in proteasomal degradation. (2009, neutral): “The decoy components contained pseudo-reversed sequences of all target proteins (Elias and Gygi, 2007; Peng et al., 2003 ).”
Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry (2007, background): “This is most simply done by reversing the target protein sequence”
Correlative GC-TOF-MS-based metabolite profiling and LC-MS-based protein profiling reveal time-related systemic regulation of metabolite–protein networks and improve pattern recognition for multiple biomarker selection (2005, methodology): “3 (Peng et al., 2003) for hits with at least two different peptides.”
Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, positive): “Target-decoy-based FDR estimates (Elias and Gygi, 2007; Peng et al., 2003) were performed using a linear discriminant analysis (LDA) method utilizing XCorr, deltaCN, missed cleavages, PPM, peptide length, and charge state as features.”
Less label, more free: Approaches in label‐free quantitative mass spectrometry (2011, positive): “This can be achieved using randomised, reversed, or decoy databases, the latter being a list of any incorrect sequences [78–80].”