ArticleAnalytical chemistry2016
Heavy Sugar and Heavy Water Create Tunable Intact Protein Mass Increases for Quantitative Mass Spectrometry in Any Feed and Organism.
Article in Analytical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Middle-Down Mass Spectrometry Reveals Activity-Modifying Phosphorylation Barcode in a Class C G Protein-Coupled Receptor.Journal of the American Chemical Society · 2022Article
- Proteomes Are of Proteoforms: Embracing the Complexity.Proteomes · 2021Review
- High-throughput quantitative top-down proteomics.Molecular omics · 2020Review
- Top-Down Proteomics: Ready for Prime Time?Analytical chemistry · 2018Review
- Metabolic labeling in middle-down proteomics allows for investigation of the dynamics of the histone code.Epigenetics & chromatin · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Stable isotope labeling techniques for quantitative top-down proteomics face unique challenges. These include unpredictable mass shifts following isotope labeling, which impedes analysis of unknown proteins and complex mixtures and exponentially greater susceptibility to incomplete isotope incorporation, manifesting as broadening of labeled intact protein peaks. Like popular bottom-up isotope labeling techniques, most top-down labeling methods are restricted to defined media/feed as well as amino acid auxotrophic organisms. We present a labeling method optimized for top-down proteomics that overcomes these challenges. We demonstrated this method through the spiking of
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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.