ArticleJournal of proteome research2021
Construction of Human Proteoform Families from 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Top-Down Proteomic Data.
Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Properties, Origin, and Consistency of Truncated Proteoforms Across Top-Down Proteomic Studies.Molecular & cellular proteomics : MCP · 2025Pooled it
- Proteoform-Selective Imaging of Tissues Using Mass Spectrometry.Angewandte Chemie (International ed. in English) · 2022Article
- The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms.Nucleic acids research · 2022Article
- Internal Fragment Ions Disambiguate and Increase Identifications in Top-Down Proteomics.Journal of proteome research · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Identification of proteoforms, the different forms of a protein, is important to understand biological processes. A proteoform family is the set of different proteoforms from the same gene. We previously developed the software program Proteoform Suite, which constructs proteoform families and identifies proteoforms by intact-mass analysis. Here, we have applied this approach to top-down proteomic data acquired at the National High Magnetic Field Laboratory 21 tesla Fourier transform ion cyclotron resonance mass spectrometer (data available on the MassIVE platform with identifier MSV000085978). We explored the ability to construct proteoform families and identify proteoforms from the high mass accuracy data that this instrument provides for a complex cell lysate sample from the MCF-7 human breast cancer cell line. There were 2830 observed experimental proteforms, of which 932 were identified, 44 were ambiguous, and 1854 were unidentified. Of the 932 unique identified proteoforms, 766 were identified by top-down MS2 analysis at 1% false discovery rate (FDR) using TDPortal, and 166 were additional intact-mass identifications (∼4.7% calculated global FDR) made using Proteoform Suite. We recently published a proteoform level schema to represent ambiguity in proteoform identifications. We implemented this proteoform level classification in Proteoform Suite for intact-mass identifications, which enables users to determine the ambiguity levels and sources of ambiguity for each intact-mass proteoform identification.
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