ArticleMolecular & cellular proteomics : MCP2018
Nonlinear Regression Improves Accuracy of Characterization of Multiplexed Mass Spectrometric Assays.
Article in Molecular & cellular proteomics : MCP, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Calibration Practices in Clinical Mass Spectrometry: Review and Recommendations.Annals of laboratory medicine · 2023Pooled it
- Protein-level batch-effect correction enhances robustness in MS-based proteomics.Nature communications · 2025Article
- Targeted proteomics addresses selectivity and complexity of protein degradation by autophagy.Autophagy · 2025Article
- Signal interference between drugs and metabolites in LC-ESI-MS quantitative analysis and its evaluation strategy.Journal of pharmaceutical analysis · 2024Article
- Proteome Discoverer-A Community Enhanced Data Processing Suite for Protein Informatics.Proteomes · 2021Review
- Low-Expressing Synucleinopathy Mouse Models Based on Oligomer-Forming Mutations and C-Terminal Truncation of α-Synuclein.Frontiers in neuroscience · 2021Article
- Matrix-Matched Calibration Curves for Assessing Analytical Figures of Merit in Quantitative Proteomics.Journal of proteome research · 2020Article
- Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance.Molecular & cellular proteomics : MCP · 2019Article
- Improving Precursor Selectivity in Data-Independent Acquisition Using Overlapping Windows.Journal of the American Society for Mass Spectrometry · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The need for assay characterization is ubiquitous in quantitative mass spectrometry-based proteomics. Among many assay characteristics, the limit of blank (LOB) and limit of detection (LOD) are two particularly useful figures of merit. LOB and LOD are determined by repeatedly quantifying the observed intensities of peptides in samples with known peptide concentrations and deriving an intensity
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.