ArticleMolecular & cellular proteomics : MCP2017
pyQms enables universal and accurate quantification of mass spectrometry data.
Article in Molecular & cellular proteomics : MCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
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- In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development.Cell reports methods · 2024Article
- AdductHunter: identifying protein-metal complex adducts in mass spectra.Journal of cheminformatics · 2024Article
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- Structure of a PSI-LHCI-cyt bProceedings of the National Academy of Sciences of the United States of America · 2018Article
- Nano LC-MS using capillary columns enables accurate quantification of modified ribonucleosides at low femtomol levels.RNA (New York, N.Y.) · 2018Article
- Establishment of Dimethyl Labeling-based Quantitative Acetylproteomics in Arabidopsis.Molecular & cellular proteomics : MCP · 2018Article
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7 authors.
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Abstract
Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm.
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