ArticlePloS one2013
Accurate LC peak boundary detection for ¹⁶O/¹⁸O labeled LC-MS data.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Quality control of imbalanced mass spectra from isotopic labeling experiments.BMC bioinformatics · 2019Article
- MZDASoft: a software architecture that enables large-scale comparison of protein expression levels over multiple samples based on liquid chromatography/tandem mass spectrometry.Rapid communications in mass spectrometry : RCM · 2015Article
- Quantitative Proteomic Approach for MicroRNA Target Prediction Based onCancer informatics · 2015Article
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Authors and funding
8 authors.
Funding
Abstract
In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.
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Registered trials
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