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Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ
Open accessAbstract
Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS signals, given that the presence of quantifiable peptides varies from sample to sample. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
MaxLFQ is a label-free LC-MS quantification method combining delayed normalization with maximal extraction of peptide ratio information across samples. In benchmark datasets it accurately recovered known protein mixing ratios, including 3:1 proteome mixes and UPS dynamic-range ratios over several orders of magnitude.
Key findings
- In a HeLa/E. coli proteome benchmark, MaxLFQ produced narrower ratio distributions and less overlap between human and E. coli proteins than spectral counting or summed peptide intensities, and most accurately recapitulated the expected 3-fold change; 3453 human and 1556 E. coli proteins were quantified.
- Statistical testing by t test outperformed fold-change ranking: at precision 0.98, 72% of E. coli proteins were recalled, and at precision 95%, 88% were retrieved with the Welch modified t test.
- For simulated smaller ratios, at 10% FDR almost all truly changing proteins were recovered at ratio 3, about half at ratio 1.6, with a strong drop below 1.6; the Q = 0.25 half-coverage point was around ratio 1.4.
- In the UPS dynamic-range benchmark, MaxLFQ was close to expected values within 2 orders of magnitude and showed increased scatter but no systematic error above 100-fold ratios; summed intensities slightly underestimated very large ratios, and spectral counts covered 2 orders of magnitude less and systematically underestimated ratios.
Methods
- Two benchmark datasets were used: (1) trypsin-digested HeLa and E. coli lysates mixed at 1:1 and 3:1 E. coli ratios, separated by isoelectric focusing into 24 fractions and analyzed in three replicates on an LTQ Orbitrap; (2) UPS1 and UPS2 standards spiked into E. coli peptides and analyzed in four replicates on a Q Exactive.
- Raw data were processed with MaxQuant/Andromeda at 1% peptide and protein FDR; match-between-runs transferred identifications across LC-MS runs, increasing quantifiable isotope patterns more than 2-fold in the proteome benchmark and by 38% in the UPS benchmark.
- MaxLFQ delayed normalization by optimizing run-specific normalization coefficients via Levenberg–Marquardt minimization of squared log fold changes, then reconstructed protein abundance profiles from pair-wise peptide ratios using median peptide ratios and least-squares fitting.
Limitations
- Stated: MaxLFQ requires a dominant population of proteins that change minimally between conditions; in the benchmark the changing E. coli population was 31% of measured proteins, which still worked but shifted the non-changing population slightly negative.
- Stated: sample-handling variability across months, machines, or laboratories remains a challenge; studies needing ultimate ratio accuracy or individual peptide quantification, such as post-translational modifications, will still rely on isotope labels, and clinical applications may benefit from spike-in references.
- Stated: computational effort grows quadratically with sample number, though a fast normalization heuristic using a graph with minimum three and average six nearest neighbors gives linear scaling; large ratios show increased scatter above 100-fold. Evident from the text: validation rests on two benchmark datasets plus an in silico downscaling experiment, not broad clinical or diverse biological validation.
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In the paper
“Spectral count ratio clouds were clearly separated only for the most abundant proteins (Figs. 3A and 3D).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“In all cases, human and E. coli proteins formed distinct clouds, but with different degrees of overlap.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Furthermore, a systematic distortion was observable that resulted in a general overestimation of the ratios of low-intensity proteins.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“It has delivered excellent performance in benchmark comparisons with other software solutions (31).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
What the sources say
- Not checked yetcites [31] Weisser, 2013, An automated pipeline for high-throughput label-free quantitative proteomics, J. Proteome Res source
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In the paper
“Transferring identifications to other LC-MS runs by matching them to unidentified features based on their masses and recalibrated retention times increased the number of quantifiable isotope patterns more than 2-fold”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
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In the paper
“Ratios of summed peptide intensities already allowed almost complete separation of human and E. coli proteins across the entire abundance range, with some overlap occurring only in the lower half (Figs. 3B and 3E).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“In particular, for low stringency there is a very rapid drop of coverage around a well-defined ratio.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“At a precision of 0.98, 72% of the E. coli proteins were recalled.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“This revealed that retrieving proteins by ratio (corresponding to a fixed fold change cut-off) was the worst strategy.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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- It may state two separate claims as one. 31
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the low-intensity region, spectral counts became discrete values, and their log ratios adopted a very wide distribution with pronounced overlap of human and E. coli proteins.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“MaxQuant identified a total of 789,978 isotope clusters through MS/MS sequencing.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“it has been validated in many and diverse biological projects.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The computational effort for this procedure grows quadratically with the number of samples to be compared”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The computational effort grows quadratically with the number of samples in which a protein is present; however, it is readily parallelizable at the protein level.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Our algorithms can handle very large experiments of 500+ samples in a manageable computing time.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, protein groups had to be unambiguously assignable to one species; this was the case for 3453 human and 1556 E. coli proteins (supplemental Table S1).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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In the paper
“Both versions of the t test performed significantly better, and the Welch modified t test was slightly better than the standard t test.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one. The quote only partly states this claim.
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In the paper
“which demonstrated that MaxLFQ performed best not only by generating the narrowest distributions, but also by most accurately recapitulating the expected fold change of three between the population averages.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Illustrating this, in our dynamic-range benchmark dataset we recorded one of the largest published E. coli proteomes so far, resulting in a high sequence coverage and hence a very narrow cloud of E. coli protein quantifications.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
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In the paper
“In the sample of E. coli plus UPS2, 15 of the lower abundant human UPS proteins were never sequenced by MS/MS, but 10 of them could be identified and quantified in at least some of the replicates through matching to the UPS1-containing samples.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“We found that this stabilized the general ratio trend and reduced the outlier sensitivity.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Spectral counts covered 2 orders of magnitude less than intensity-based methods, because there were no MS/MS events for all proteins of the lowest two abundance groups in all UPS2-plus-E. coli samples (Fig. 6D).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“For ratios of more than 100-fold, we detected increased scatter, but no systematic error that would lead to an over- or underestimation of the ratio (Fig. 6F).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“The center of the 1:1 population is shifted to slightly negative values.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: A majority population of proteins exists that is not changing between the samples, so average behavior can be used as a relative standard.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“UPS proteins are clearly separated from the narrow cloud of E. coli proteins and cluster in groups according to their relative abundances.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“When we used our MaxLFQ algorithm, the overlap of the populations was further reduced relative to the summed intensity approach, and the number of extreme outliers was markedly reduced (Figs. 3C and 3F).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Summed intensities yielded very similar results within 2 orders of magnitude (Fig. 6C) but a small systematic underestimation of very large ratios (Fig. 6G).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The Wilcoxon–Mann–Whitney test performed better but also had problems at low recall.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Then we rescale the whole profile to the cumulative intensity across samples, thereby preserving the total summed intensity for a protein over all samples”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Although high mass accuracy aids in the identification of peptides (42), it is the high mass resolution that is crucial to accurate quantification. This is because the accurate determination of extracted ion currents (XICs) of peptides is critical for comparison between samples (43).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
What the sources say
- Not checked yetcites [42] Cox, 2008, MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification, Nat. Biotechnol source
- Not checked yetcites [43] Andersen, 2003, Proteomic characterization of the human centrosome by protein correlation profiling, Nature source
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In the paper
“We want to use only common peptides for pair-wise ratio determination without losing scalability for large numbers of samples.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Conversely, any up-front separation of proteins or peptides potentially poses serious problems in a label-free approach, because the partitioning into fractions is prone to change slightly in the analysis of different samples.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“Both were also extracted by MaxQuant, so we do not introduce biases due to the search engine and the set of identified peptides, and only benchmark conceptually different metrics of quantification.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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In the paper
“Most methods require measurement of samples under uniform conditions with strict adherence to standard sample-handling procedures, with minimal fractionation and in tight temporal sequence.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
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In the paper
“In addition, there is no limit on the number of samples that can be compared, in contrast to the finite number of “plexes” available for label-based methods (7).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
What the sources say
- Not checked yetcites [7] Dephoure, 2012, Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast, Sci. Signal source
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In the paper
“Due to stochastic MS/MS sequencing and differences in protein abundances across samples, peptide identifications are often missing in specific samples.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“When isotope labels are introduced early in the workflow, samples can be mixed, and any sample-handling issues equally affect all proteins or peptides. This allows complex biochemical workflows without loss of quantitative accuracy.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Finally, the modest accuracy of their quantitative readouts relative to those obtained with stable-isotope-based methods often prohibits their use for biological questions that require the detection of small changes, such as proteome changes upon stimulus.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The normalization is done purely from the data obtained and without the addition of external quantification standards or reliance on a fixed set of “housekeeping” proteins.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: A majority population of proteins exists that is not changing between the samples, so average behavior can be used as a relative standard.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Label-free quantification is in principle applicable to any kind of sample, including materials that cannot be directly metabolically labeled (for instance, many clinical samples).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In the resulting six samples all human proteins therefore should have had one-to-one ratios and all E. coli proteins should have had a ratio of three to one between replicate groups.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is compatible with standard statistical analysis workflows”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At this point we have constructed a triangular matrix containing all pair-wise protein ratios between any two samples, which is the maximal possible quantification information.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“High mass resolution and accuracy and high peptide identification rates have been key ingredients in the success of isotope-label-based methods. These factors contribute similarly to the quality of label-free quantification.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The pair-wise protein ratio rCB (Fig. 2D) is then defined as the median of the peptide ratios, to protect against outliers.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Instead, ratios derived from individual peptide signals should be taken into account, rather than a sum of intensities, because the XIC ratios for each peptide are already a measurement of the protein ratio.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Chemical labeling (39–41) is in principle universally applicable, but because the labels are introduced later in the sample processing, some of the advantages in robustness are lost.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > Abstract
What the sources say
- Not checked yetcites [39] Gygi, 1999, Quantitative analysis of complex protein mixtures using isotope-coded affinity tags, Nat. Biotechnol source
- Not checked yetcites [40] Ross, 2004, Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents, Mol. Cell. Proteomics source
- Not checked yetcites [41] Boersema, 2008, Triplex protein quantification based on stable isotope labeling by peptide dimethylation applied to cell and tissue lysates, Proteomics source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Such ratios typically occur in the context of interaction proteomics experiments (56), where early mixing of isotope-labeled samples is usually not possible and some of the principal advantages of metabolic labeling are therefore lost.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
What the sources say
- Not checked yetcites [56] Hubner, 2010, Quantitative proteomics combined with BAC TransgeneOmics reveals in vivo protein interactions, J. Cell Biol source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is presumably because in the benchmark dataset all true ratios were either 1:1 or 1:3, whereas in real applications the true ratio distribution has a dense spectrum of small changes.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In large pulldown datasets, the background population does not have to be the same over all samples and can be a different one in each pair-wise sample comparison in MaxLFQ.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear? Based: unclearIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This demonstrates a clear advantage of intensity-based approaches.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The ease of use of MaxLFQ as part of the MaxQuant software suite should enable our technology to be widely adopted by nonspecialized labs as well.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The advantage of permutation-based methods is that no assumptions need to be made regarding the parametric distributions of intensities or ratios.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, this had no effect on subsequent tests for finding differentially expressed proteins, as they are all insensitive to global shifts of all values.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“As a means to control the FDR and solve potential multiple hypothesis testing problems in real biological datasets, we usually apply permutation-based methods for calculating q-values and global FDRs.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
What the sources say
- Not checked yetcites [55] Tusher, 2001, Significance analysis of microarrays applied to the ionizing radiation response, Proc. Natl. Acad. Sci. U.S.A source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Extreme ratios typically coincide with very different peptide populations identified in the samples to be compared: many in the sample with high protein abundance, of which only a small subset is found in the low-abundance sample. This can make the protein ratio determination rely on very few quantification events, which increases the sensitivity to outliers.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, applications that require extreme robustness, such as sample handling in a clinical setting, will likely benefit from spike-in references that serve as internal standards.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Biological studies that depend on the ultimate accuracy of the ratio readout or on quantitative information about individual peptides, such as post-translationally modified ones, will still rely on isotope labels.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Label-free quantification benefits dramatically from this depth, as it increases the number of quantifiable features present in a given LC-MS run and allows averaging over more peptides for protein quantification.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Recent advances in mass spectrometer hardware (76, 77) have provided a boost in the depth of standard analyses and enabled near-complete model proteome quantification in minimal measuring time (6).”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > DISCUSSION
What the sources say
- Not checked yetcites [76] Michalski, 2012, Ultra high resolution linear ion trap Orbitrap mass spectrometer (Orbitrap Elite) facilitates top down LC MS/MS and versatile peptide fragmentation modes, Mol. Cell. Proteomics source
- Not checked yetcites [77] Michalski, 2011, Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer, Mol. Cell. Proteomics source
- Not checked yetcites [6] Mann, 2013, The coming age of complete, accurate, and ubiquitous proteomes, Mol. Cell source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In datasets of practical interest, the true proportion of false positives is not known a priori.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This quantity contains a sum running over all pairs of samples that grows quadratically with the number of samples.”
§ Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The authors state this as an assumption.
A majority population of proteins exists that is not changing between the samples, so average behavior can be used as a relative standard.
“We exploit the fact that the majority of the proteome typically does not change between any two conditions so that the average behavior can be used as a relative standard.”
“MaxLFQ has the prerequisite that a majority population of proteins exists that is not changing between the samples.”
“normalization was based on the assumption of a dominating population of non-changing proteins.”
The authors state this as an assumption.
A dominant population of proteins changes minimally between experimental conditions.
“The only prerequisite is a dominant population of proteins that change minimally between experimental conditions.”
The authors state this as an assumption.
A large overlap of peptides between samples can be interpreted as a small distance between them.
“A large overlap of peptides between each pair of nodes was interpreted as a small distance between them.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“LFQ intensities are normalized median mass spectra intensity values that allow this quantification to be performed with any peptide and protein fractionation while maintaining high accuracy (Cox et al., 2014).”
From Defining the Adult Neural Stem Cell Niche Proteome Identifies Key Regulators of Adult Neurogenesis (2020) · cites this paper as Cox et al., 2014
Citations
Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Self-citationIn silico prediction of protein-protein interactions in human macrophages
Souiai, O., Guerfali, F. Z., Miled, S. B., Brun, C., & Benkahla, A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-157 · Cited by 10,785
Significance analysis of microarrays applied to the ionizing radiation response
Tusher, V. G., Tibshirani, R., & Chu, G. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091062498 · Cited by 10,568
Numerical Recipes, The Art of Scientific Computing
Press, W. H., Flannery, B. P., Teukolsky, S. A., Vetterling, W. T., & Gould, H. (1987) · American Journal of Physics · doi:10.1119/1.14981 · Cited by 10,032
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Self-citationNumerical Recipes: The Art of Scientific Computing
Ziegel, E. R., Press, W. H., Flannery, B. P., Teukolsky, S. A., & Vetterling, W. T. (1987) · Technometrics · doi:10.2307/1269484 · Cited by 6,704
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Self-citationAndromeda: A Peptide Search Engine Integrated into the MaxQuant Environment
Cox, J., Neuhauser, N., Michalski, A., Scheltema, R. A., Olsen, J. V., & Mann, M. (2011) · Journal of Proteome Research · doi:10.1021/pr101065j · Cited by 5,503
Self-citationQuantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
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van der Reest, J., Lilla, S., Zheng, L., Zanivan, S. R., & Gottlieb, E. (2018) · Nature Communications · doi:10.1038/s41467-018-04003-3 · Cited by 273
Activation of the ATR kinase by the RPA-binding protein ETAA1
Haahr, P., Hoffmann, S., Tollenaere, M. A. X., Ho, T., Toledo, L. I., Mann, M., Bekker‐Jensen, S., Räschle, M., & Mailand, N. (2016) · Nature Cell Biology · doi:10.1038/ncb3422 · Cited by 272
Self-citationAn evaluation of blood compatibility of silver nanoparticles
Huang, H., Lai, W., Cui, M., Liang, L., Lin, Y., Fang, Q., Liu, Y., & Xie, L. (2016) · Scientific Reports · doi:10.1038/srep25518 · Cited by 186
Ottman, N., Davids, M., Suarez-Diez, M., Boeren, S., Schaap, P. J., Martins dos Santos, V. A. P., Smidt, H., Belzer, C., & de Vos, W. M. (2017) · Applied and Environmental Microbiology · doi:10.1128/aem.01014-17 · Cited by 269
Visualization of LC‐MS/MS proteomics data in MaxQuant
Tyanova, S., Temu, T., Carlson, A., Sinitcyn, P. G., Mann, M., & Cox, J. (2015) · PROTEOMICS · doi:10.1002/pmic.201400449 · Cited by 268
Self-citationPhosphoproteomics in the Age of Rapid and Deep Proteome Profiling
Riley, N. M., & Coon, J. J. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04123 · Cited by 265
Comprehensive Proteomic Analysis of Human Erythropoiesis
Gautier, E., Ducamp, S., Leduc, M., Salnot, V., Guillonneau, F., Dussiot, M., Hale, J., Giarratana, M., Raimbault, A., Douay, L., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.06.085 · Cited by 265
Née, G., Kramer, K., Nakabayashi, K., Yuan, B., Xiang, Y., Miatton, E., Finkemeier, I., & Soppe, W. J. J. (2017) · Nature Communications · doi:10.1038/s41467-017-00113-6 · Cited by 265
Mitochondrial Protein Interaction Mapping Identifies Regulators of Respiratory Chain Function
Floyd, B. J., Wilkerson, E., Veling, M. T., Minogue, C. E., Xia, C., Beebe, E. T., Wrobel, R. L., Cho, H., Kremer, L. S., Alston, C. L., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.06.033 · Cited by 264
Zhang, X., Deeke, S. A., Ning, Z., Starr, A. E., Butcher, J., Li, J. S. Y., Mayne, J., Cheng, K., Liao, B., Li, L., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05357-4 · Cited by 263
Neufeld-Cohen, A., Robles, M. S., Aviram, R., Manella, G., Adamovich, Y., Ladeuix, B., Nir, D., Rousso-Noori, L., Kuperman, Y., Golik, M., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1519650113 · Cited by 262
Self-citationSchiller, H. B., Fernandez, I. E., Burgstaller, G., Schaab, C., Scheltema, R. A., Schwarzmayr, T., Strom, T. M., Eickelberg, O., & Mann, M. (2015) · Molecular Systems Biology · doi:10.15252/msb.20156123 · Cited by 261
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Zhu, Y., Clair, G., Chrisler, W., Shen, Y., Zhao, R., Shukla, A. K., Moore, R., Misra, R. S., Pryhuber, G., Smith, R. D., et al. (2018) · Angewandte Chemie International Edition · doi:10.1002/anie.201802843 · Cited by 261
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Marmor-Kollet, H., Siany, A., Kedersha, N., Knafo, N., Rivkin, N., Danino, Y. M., Moens, T. G., Olender, T., Sheban, D., Cohen, N., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.10.032 · Cited by 259
Green, D. S., Colgan, T. J., Thompson, R. C., & Carolan, J. C. (2018) · Environmental Pollution · doi:10.1016/j.envpol.2018.12.017 · Cited by 255
Müller, P. M., Rademacher, J., Bagshaw, R. D., Wortmann, C., Barth, C., van Unen, J., Alp, K. M., Giudice, G., Eccles, R. L., Heinrich, L. E., et al. (2020) · Nature Cell Biology · doi:10.1038/s41556-020-0488-x · Cited by 253
Escoll, P., Song, O., Viana, F., Steiner, B., Lagache, T., Olivo‐Marín, J., Impens, F., Brodin, P. M., Hilbi, H., & Buchrieser, C. (2017) · Cell Host & Microbe · doi:10.1016/j.chom.2017.07.020 · Cited by 252
MaxDIA enables library-based and library-free data-independent acquisition proteomics
Sinitcyn, P. G., Hamzeiy, H., Soto, F. S., Itzhak, D. N., McCarthy, F., Wichmann, C., Steger, M., Ohmayer, U., Distler, U., Kaspar‐Schoenefeld, S., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00968-7 · Cited by 252
Self-citationPham, T. C., Jayasinghe, M. K., Pham, T. T., Yang, Y., Wei, L., Usman, W. M., Chen, H., Pirisinu, M., Gong, J., Kim, S., et al. (2021) · Journal of Extracellular Vesicles · doi:10.1002/jev2.12057 · Cited by 250
The cytotoxic T cell proteome and its shaping by the kinase mTOR
Hukelmann, J. L., Anderson, K. E., Sinclair, L. V., Grzes, K. M., Murillo, A. B., Hawkins, P. T., Stephens, L. R., Lamond, A. I., & Cantrell, D. A. (2016) · Nature Immunology · doi:10.1038/ni.3314 · Cited by 249
Yang, D., Jacobson, A. R., Meerschaert, K. A., Sifakis, J. J., Wu, M., Chen, X., Yang, T., Zhou, Y., Anekal, P. V., Rucker, R. A., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.024 · Cited by 248
Deusch, S., Camarinha‐Silva, A., Conrad, J., Beifuß, U., Rodehutscord, M., & Seifert, J. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.01605 · Cited by 248
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Lasonder, E., Rijpma, S. R., van Schaijk, B. C. L., Hoeijmakers, W. A. M., Kensche, P. R., Gresnigt, M. S., Italiaander, A., Vos, M. W., Woestenenk, R., Bousema, T., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw536 · Cited by 243
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Geyer, P. E., Albrechtsen, N. J. W., Tyanova, S., Graßl, N., Iepsen, E. W., Lundgren, J. R., Madsbad, S., Holst, J. J., Torekov, S. S., & Mann, M. (2016) · Molecular Systems Biology · doi:10.15252/msb.20167357 · Cited by 241
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Drummond, E., Nayak, S., Faustin, A., Pires, G., Hickman, R. A., Askenazi, M., Cohen, M., Haldiman, T., Kim, C., Han, X., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1691-0 · Cited by 239
Proteome complexity and the forces that drive proteome imbalance
Harper, J. W., & Bennett, E. J. (2016) · Nature · doi:10.1038/nature19947 · Cited by 239
Pan-cancer proteomic map of 949 human cell lines
Gonçalves, E., Poulos, R. C., Cai, Z., Barthorpe, S., Manda, S. S., Lucas, N., Beck, A., Bucio-Noble, D., Dausmann, M., Hall, C., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.06.010 · Cited by 239
Chen, S., Liu, X., Peng, C., Tan, C., Sun, H., Liu, H., Zhang, Y., Wu, P., Cui, C., Liu, C., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.02.007 · Cited by 238
Arginine phosphorylation marks proteins for degradation by a Clp protease
Trentini, D. B., Suskiewicz, M. J., Heuck, A., Kurzbauer, R., Deszcz, L., Mechtler, K., & Clausen, T. (2016) · Nature · doi:10.1038/nature20122 · Cited by 241
Hyenne, V., Ghoroghi, S., Collot, M., Bons, J., Follain, G., Harlepp, S., Mary, B., Bauer, J., Mercier, L., Busnelli, I., et al. (2019) · Developmental Cell · doi:10.1016/j.devcel.2019.01.014 · Cited by 237
Li, Y., Lih, T. M., Dhanasekaran, S. M., Mannan, R., Chen, L., Cieslik, M. P., Wu, Y., Lu, R. J.-H., Clark, D. J., Kołodziejczak, I., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.12.001 · Cited by 237
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Derks, J., Leduc, A., Wallmann, G., Huffman, R. G., Willetts, M., Khan, S., Specht, H., Ralser, M., Demichev, V., & Slavov, N. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01389-w · Cited by 234
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Platanitis, E., Demiroz, D., Schneller, A., Fischer, K., Capelle, C., Hartl, M., Gossenreiter, T., Müller, M., Novatchkova, M., & Decker, T. (2019) · Nature Communications · doi:10.1038/s41467-019-10970-y · Cited by 233
Proteomics reveals dynamic assembly of repair complexes during bypass of DNA cross-links
Räschle, M., Smeenk, G., Hansen, R. K., Temu, T., Oka, Y., Hein, M. Y., Nagaraj, N., Long, D. T., Walter, J. C., Hofmann, K., et al. (2015) · Science · doi:10.1126/science.1253671 · Cited by 231
Self-citationWillforss, J., Chawade, A., & Levander, F. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00523 · Cited by 231
Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome
Graßl, N., Kulak, N. A., Pichler, G., Geyer, P. E., Jung, J., Schubert, S., Sinitcyn, P. G., Cox, J., & Mann, M. (2016) · Genome Medicine · doi:10.1186/s13073-016-0293-0 · Cited by 229
Self-citationPurification of cross-linked RNA-protein complexes by phenol-toluol extraction
Urdaneta, E. C., Vieira-Vieira, C. H., Hick, T., Wessels, H.-H., Figini, D., Moschall, R., Medenbach, J., Ohler, U., Granneman, S., Selbach, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08942-3 · Cited by 228
Differential dynamics of the mammalian mRNA and protein expression response to misfolding stress
Cheng, Z., Teo, G., Krueger, S., Rock, T. M., Koh, H. W., Choi, H., & Vogel, C. (2016) · Molecular Systems Biology · doi:10.15252/msb.20156423 · Cited by 227
Activity-dependent neuroprotective protein recruits HP1 and CHD4 to control lineage-specifying genes
Ostapcuk, V., Mohn, F., Carl, S. H., Basters, A., Heß, D., Iešmantavičius, V., Lampersberger, L., Flemr, M., Pandey, A., Thomä, N. H., et al. (2018) · Nature · doi:10.1038/s41586-018-0153-8 · Cited by 227
Keshishian, H., Burgess, M. W., Gillette, M. A., Mertins, P., Clauser, K. R., Mani, D. R., Kuhn, E. W., Farrell, L. A., Gerszten, R. E., & Carr, S. A. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.046813 · Cited by 222
Beltran, P. M. J., Federspiel, J. D., Sheng, X., & Cristea, I. M. (2017) · Molecular Systems Biology · doi:10.15252/msb.20167062 · Cited by 218
RNA localization is a key determinant of neurite-enriched proteome
Zappulo, A., van den Bruck, D., Mattioli, C. C., Franke, V., Imami, K., McShane, E., Moreno‐Estellés, M., Calviello, L., Filipchyk, A., Peguero-Sánchez, E., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00690-6 · Cited by 217
Necroptosis promotes cell-autonomous activation of proinflammatory cytokine gene expression
Zhu, K., Liang, W. P., Ma, Z., Xu, D., Cao, S., Lu, X., Liu, N., Shan, B., Qian, L., & Yuan, J. (2018) · Cell Death and Disease · doi:10.1038/s41419-018-0524-y · Cited by 217
Garzia, A., Jafarnejad, S. M., Meyer, C., Chapat, C., Gogakos, T., Morozov, P. S., Amiri, M., Shapiro, M., Molina, H., Tuschl, T., et al. (2017) · Nature Communications · doi:10.1038/ncomms16056 · Cited by 216
Malonylation of GAPDH is an inflammatory signal in macrophages
Galván-Peña, S., Carroll, R. G., Newman, C. F., Hinchy, E. C., Pålsson‐McDermott, E. M., Robinson, E. K., Covarrubias, S., Nadin, A. J., James, A. M., Haneklaus, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08187-6 · Cited by 220
Separable roles for Mycobacterium tuberculosis ESX-3 effectors in iron acquisition and virulence
Tufariello, J. M., Chapman, J. R., Kerantzas, C. A., Wong, K.-W., Vilchèze, C., Jones, C. M., Cole, L. E., Tinaztepe, E., Thompson, V., Fenyö, D., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1523321113 · Cited by 215
An effector from the Huanglongbing-associated pathogen targets citrus proteases
Clark, K. J., Franco, J., Schwizer, S., Pang, Z., Hawara, E., Liebrand, T. W. H., Pagliaccia, D., Zeng, L., Gurung, F. B., Wang, P., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04140-9 · Cited by 213
Shah, A. D., Goode, R. J. A., Huang, C., Powell, D., & Schittenhelm, R. B. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00496 · Cited by 213
Wingo, A. P., Dammer, E. B., Breen, M. S., Logsdon, B. A., Duong, D. M., Troncosco, J. C., Thambisetty, M., Beach, T. G., Serrano, G. E., Reiman, E. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09613-z · Cited by 211
Coscia, F., Watters, K. M., Curtis, M., Eckert, M. A., Chiang, C. Y., Tyanova, S., MONTAG, A. G., Lastra, R. R., Lengyel, E. R., & Mann, M. (2016) · Nature Communications · doi:10.1038/ncomms12645 · Cited by 210
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Jiang, Y., Balaya, R. D. A., Schuster, D., Neely, B. A., Rosano, G. L., Volkmar, N., Momenzadeh, A., Peters-Clarke, T. M., Egbert, S., Kreimer, S. D., et al. (2024) · ACS Measurement Science Au · doi:10.1021/acsmeasuresciau.3c00068 · Cited by 217
The proteome landscape of the kingdoms of life
Müller, J., Geyer, P. E., Colaço, A. R., Treit, P. V., Strauss, M. T., Oroshi, M., Doll, S., Winter, S. V., Bader, J. M., Köhler, N., et al. (2020) · Nature · doi:10.1038/s41586-020-2402-x · Cited by 209
Self-citationKöster, S., Upadhyay, S., Chandra, P., Papavinasasundaram, K., Yang, G., Hassan, A., Grigsby, S. J., Mittal, E., Park, H. S., Jones, V., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707792114 · Cited by 208
Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes
Virant‐Klun, I., Leicht, S., Hughes, C., & Krijgsveld, J. (2016) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.056887 · Cited by 207
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Bielow, C., Mastrobuoni, G., & Kempa, S. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00780 · Cited by 204
Single organelle function and organization as estimated from Arabidopsis mitochondrial proteomics
Fuchs, P., Rugen, N., Carrie, C., Elsässer, M., Finkemeier, I., Giese, J., Hildebrandt, T. M., Kühn, K., Maurino, V. G., Ruberti, C., et al. (2019) · The Plant Journal · doi:10.1111/tpj.14534 · Cited by 204
Schopp, I. M., Ramirez, C. C. A., Debeljak, J., Kreibich, E., Skribbe, M., Wild, K., & Béthune, J. (2017) · Nature Communications · doi:10.1038/ncomms15690 · Cited by 203
Cytosolic Protein Vms1 Links Ribosome Quality Control to Mitochondrial and Cellular Homeostasis
Izawa, T., Park, S.-H., Zhao, L., Hartl, F. U., & Neupert, W. (2017) · Cell · doi:10.1016/j.cell.2017.10.002 · Cited by 203
A time-resolved proteomic and prognostic map of COVID-19
Demichev, V., Tober-Lau, P., Lemke, O., Nazarenko, T., Thibeault, C., Whitwell, H., Röhl, A., Freiwald, A., Szyrwiel, L., Ludwig, D., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.005 · Cited by 200
A streamlined mass spectrometry–based proteomics workflow for large-scale FFPE tissue analysis
Coscia, F., Doll, S., Bech, J. M., Schweizer, L., Mund, A., Lengyel, E., Lindebjerg, J., Madsen, G. I., Moreira, J. M., & Mann, M. (2020) · The Journal of Pathology · doi:10.1002/path.5420 · Cited by 200
Self-citationMetaPro-IQ: a universal metaproteomic approach to studying human and mouse gut microbiota
Zhang, X., Ning, Z., Mayne, J., Moore, J. I., Li, J. S. Y., Butcher, J., Deeke, S. A., Chen, R., Chiang, C., Wen, M., et al. (2016) · Microbiome · doi:10.1186/s40168-016-0176-z · Cited by 200
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Lazarovits, J., Sindhwani, S., Tavares, A. J., Zhang, Y., Song, F., Audet, J., Krieger, J. R., Syed, A. M., Stordy, B. P., & Chan, W. C. W. (2019) · ACS Nano · doi:10.1021/acsnano.9b02774 · Cited by 199
Structure of the human 26S proteasome at a resolution of 3.9 Å
Schweitzer, A., Aufderheide, A., Rudack, T., Beck, F., Pfeifer, G., Plitzko, J. M., Sakata, E., Schulten, K. J., Förster, F. G., & Baumeister, W. P. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608050113 · Cited by 198
Relative and Absolute Quantitation in Mass Spectrometry–Based Proteomics
Ankney, J. A., Muneer, A., & Chen, X. (2018) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-061516-045357 · Cited by 198
Wai, T., Saita, S., Nolte, H., Müller, S., König, T., Richter‐Dennerlein, R., Sprenger, H., Madrenas, J., Mühlmeister, M., Brandt, U., et al. (2016) · EMBO Reports · doi:10.15252/embr.201642698 · Cited by 197
Hu, J., Wang, S., Hou, Y., Chen, Z., Liu, L., Li, R., Li, N., Zhou, L., Yang, Y., Wang, L., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01662-5 · Cited by 207
Hsieh, Y.-C., Guo, C., Yalamanchili, H. K., Abreha, M., Al-Ouran, R., Li, Y., Dammer, E. B., Lah, J. J., Levey, A. I., Bennett, D. A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.104 · Cited by 196
Zhong, W., Myers, J. S., Wang, F., Wang, K., Lucas, J., Rosfjord, E. C., Lucas, J., Hooper, A. T., Yang, S., Lemon, L., et al. (2020) · BMC Genomics · doi:10.1186/s12864-019-6344-3 · Cited by 194
Annexin A11 is targeted by IgG4 and IgG1 autoantibodies in IgG4-related disease
Hubers, L. M., Vos, H. R., Schuurman, A. R., Erken, R., Elferink, R. P. J. O., Burgering, B. M. T., van de Graaf, S. F. J., & Beuers, U. H. (2017) · Gut · doi:10.1136/gutjnl-2017-314548 · Cited by 193
Lee, A. H., Shannon, C. P., Amenyogbe, N., Bennike, T. B., Diray‐Arce, J., Idoko, O. T., Gill, E. E., Ben-Othman, R., Pomat, W. S., van Haren, S. D., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08794-x · Cited by 192
Completion of the cytosolic post-chorismate phenylalanine biosynthetic pathway in plants
Qian, Y., Lynch, J. H., Guo, L., Rhodes, D., Morgan, J. A., & Dudareva, N. (2018) · Nature Communications · doi:10.1038/s41467-018-07969-2 · Cited by 191
E-cadherin interactome complexity and robustness resolved by quantitative proteomics
Guo, Z., Neilson, L. J., Zhong, H., Murray, P. S., Zanivan, S. R., & Zaidel‐Bar, R. (2014) · Science Signaling · doi:10.1126/scisignal.2005473 · Cited by 189
Chong, C., Marino, F., Pak, H., Racle, J., Daniel, R. T., Müller, M., Gfeller, D., Coukos, G., & Bassani‐Sternberg, M. (2017) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir117.000383 · Cited by 188
MaxQuant Software for Ion Mobility Enhanced Shotgun Proteomics
Prianichnikov, N. A., Koch, H., Koch, S., Lubeck, M., Heilig, R., Brehmer, S., Fischer, R., & Cox, J. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001720 · Cited by 184
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Blomme, A., Ford, C. A., Mui, E. J., Patel, R., Ntala, C., Jamieson, L. E., Planque, M., McGregor, G. H., Peixoto, P., Hervouet, É., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16126-7 · Cited by 184
Optimization of metabolomic data processing using NOREVA
Fu, J., Zhang, Y., Wang, Y., Zhang, H., Liu, J., Tang, J., Yang, Q., Sun, H., Qiu, W., Ma, Y., et al. (2021) · Nature Protocols · doi:10.1038/s41596-021-00636-9 · Cited by 183
Beck, S., Michalski, A., Raether, O., Lubeck, M., Kaspar, S., Goedecke, N., Baessmann, C., Hornburg, D., Meier, F., Paron, I., et al. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.047407 · Cited by 181
Self-citationBuch-Larsen, S. C., Hendriks, I. A., Lyon, D. B., Jensen, L. J., & Nielsen, M. L. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.083 · Cited by 181
Protein profile of fiber types in human skeletal muscle: a single-fiber proteomics study
Murgia, M., Nogara, L., Baraldo, M., Reggiani, C., Mann, M., & Schiaffino, S. (2021) · Skeletal Muscle · doi:10.1186/s13395-021-00279-0 · Cited by 180
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Ludwig, K. R., Schroll, M. M., & Hummon, A. B. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00235 · Cited by 179
Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology
Aretz, I., & Meierhofer, D. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17050632 · Cited by 178
Proteome-Wide Evaluation of Two Common Protein Quantification Methods
O’Connell, J. D., Paulo, J. A., O’Brien, J. J., & Gygi, S. P. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00016 · Cited by 178
A comparative study of evaluating missing value imputation methods in label-free proteomics
Jin, L., Bi, Y., Hu, C., Qu, J., Shen, S., Wang, X., & Tian, Y. (2021) · Scientific Reports · doi:10.1038/s41598-021-81279-4 · Cited by 178
Ubiquitination regulates ER-phagy and remodelling of endoplasmic reticulum
González, A., Covarrubias‐Pinto, A., Bhaskara, R. M., Glogger, M., Kuncha, S. K., Xavier, A., Seemann, E. A., Misra, M., Hoffmann, M. E., Bräuning, B., et al. (2023) · Nature · doi:10.1038/s41586-023-06089-2 · Cited by 183
Subcellular transcriptomes and proteomes of developing axon projections in the cerebral cortex
Poulopoulos, A., Murphy, A. J., Özkan, A., Davis, P. W., Hatch, J. J., Kirchner, R., & Macklis, J. D. (2019) · Nature · doi:10.1038/s41586-018-0847-y · Cited by 177
PROTAC-mediated degradation reveals a non-catalytic function of AURORA-A kinase
Adhikari, B., Božilović, J., Diebold, M., Schwarz, J. D., Hofstetter, J., Schröder, M., Wanior, M., Narain, A., Vogt, M., Stanković, N. D., et al. (2020) · Nature Chemical Biology · doi:10.1038/s41589-020-00652-y · Cited by 180
Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome
Rosenberger, F. A., Thielert, M., Strauss, M. T., Schweizer, L., Ammar, C., Mädler, S. C., Metousis, A., Skowronek, P., Wahle, M., Madden, K., et al. (2023) · Nature Methods · doi:10.1038/s41592-023-02007-6 · Cited by 176
Self-citationDeshmukh, A. S., Peijs, L., Beaudry, J. L., Jespersen, N. Z., Nielsen, C. H., Ma, T., Brunner, A., Larsen, T. J., Bayarri‐Olmos, R., Prabhakar, B. S., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.10.001 · Cited by 176
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Ratto, E., Chowdhury, S., Siefert, N., Schneider, M., Wittmann, M., Helm, D., & Palm, W. (2022) · Nature Communications · doi:10.1038/s41467-022-32515-6 · Cited by 175
Lorenz, C., Lesimple, P., Bukowiecki, R., Zink, A., Inak, G., Mlody, B., Singh, M., Semtner, M., Mah, N., Auré, K., et al. (2017) · Cell stem cell · doi:10.1016/j.stem.2016.12.013 · Cited by 174
Deshmukh, A. S., Steenberg, D. E., Hostrup, M., Birk, J. B., Larsen, J. K., Santos, A., Kjøbsted, R., Hingst, J. R., Schéele, C., Murgia, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20556-8 · Cited by 174
Self-citationCell-Type-Resolved Quantitative Proteomics of Murine Liver
Azimifar, S. B., Nagaraj, N., Cox, J., & Mann, M. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.11.002 · Cited by 173
Self-citationBianchi, G., Martella, R., Ravera, S., Marini, C., Capitanio, S., Orengo, A., Emionite, L., Lavarello, C., Amaro, A., Petretto, A., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.3688 · Cited by 173
Loss-less Nano-fractionator for High Sensitivity, High Coverage Proteomics
Kulak, N. A., Geyer, P. E., & Mann, M. (2017) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o116.065136 · Cited by 173
Self-citation
Metadata
- Authors
- Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M.
- Affiliations
- Max Planck Institute of Biochemistry (DE)
- Corresponding author
- Cox, Jürgen
- Mann, Matthias
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 13
- Issue
- 9
- Pages
- 2513-2526
- ISSN
- 1535-9476 (ISSN-L)
- PMC
- PMC4159666
- OpenAlex
- W2170776626
- Semantic Scholar
- dc7f01616aea5d85e594d6b9d1113ca3bb292d28
- Cited by
- 5,180
- References
- 80
- Citations by year
- 2026: 369 · 2025: 513 · 2024: 583 · 2023: 558 · 2022: 512 · 2021: 561 · 2020: 550 · 2019: 448 · 2018: 402 · 2017: 299 · 2016: 245 · 2015: 111 · 2014: 24
- FWCI
- 97.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Molecular & Cellular Proteomics (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Keywords
- label-free quantification, MaxQuant
- MeSH terms
- Algorithms, Escherichia coli, HeLa Cells, Humans, Peptides, Proteins, Software, Proteome, Proteomics
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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