Topic
Quantitative proteomics
About: Quantitative proteomics is a research topic. Over the lifetime, 3769 publications have been published within this topic receiving 180120 citations.
Papers published on a yearly basis
Papers
TL;DR: MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data, detects peaks, isotope clusters and stable amino acid isotope–labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space and achieves mass accuracy in the p.p.b. range.
Abstract: Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
15,064 citations
TL;DR: SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system and is applied to the relative quantitation of changes in protein expression during the process of muscle cell differentiation.
6,116 citations
TL;DR: An approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures based on isotope-coded affinity tags and tandem mass spectrometry is described.
Abstract: We describe an approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures. The method is based on a class of new chemical reagents termed isotope-coded affinity tags (ICATs) and tandem mass spectrometry. Using this strategy, we com- pared protein expression in the yeast Saccharomyces cerevisiae, using either ethanol or galactose as a carbon source. The measured differences in protein expression correlated with known yeast metabolic function under glucose-repressed conditions. The method is redundant if multiple cysteinyl residues are present, and the relative quantification is highly accurate because it is based on stable isotope dilution techniques. The ICAT approach should provide a widely applicable means to compare quantitatively glob- al protein expression in cells and tissues.
5,159 citations
TL;DR: A new intensity determination and normalization procedure called MaxLFQ is developed that is fully compatible with any peptide or protein separation prior to LC-MS analysis, which accurately detects the mixing ratio over the entire protein expression range, with greater precision for abundant proteins.
4,939 citations
TL;DR: An integrated approach to build, test, and refine a model of a cellular pathway, in which perturbations to critical pathway components are analyzed using DNA microarrays, quantitative proteomics, and databases of known physical interactions, suggests hypotheses about the regulation of galactose utilization and physical interactions between this and a variety of other metabolic pathways.
Abstract: We demonstrate an integrated approach to build, test, and refine a model of a cellular pathway, in which perturbations to critical pathway components are analyzed using DNA microarrays, quantitative proteomics, and databases of known physical interactions. Using this approach, we identify 997 messenger RNAs responding to 20 systematic perturbations of the yeast galactose-utilization pathway, provide evidence that approximately 15 of 289 detected proteins are regulated posttranscriptionally, and identify explicit physical interactions governing the cellular response to each perturbation. We refine the model through further iterations of perturbation and global measurements, suggesting hypotheses about the regulation of galactose utilization and physical interactions between this and a variety of other metabolic pathways.
2,232 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 2 |
| 2025 | 30 |
| 2024 | 70 |
| 2023 | 124 |
| 2022 | 190 |
| 2021 | 289 |