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PXD035637 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleSampling the proteome by emerging single-molecule and mass-spectrometry based methods
DescriptionMammalian cells have about 25,000-fold more protein molecules than mRNA molecules. This larger number of molecules and the associated larger dynamic range have major implications in the application of proteomics technologies. We examine these implications for both liquid chromatography-tandem mass-spectrometry (LC-MS/MS) and single-molecule counting and provide estimates on how many molecules are routinely measured in proteomics experiments by LC-MS/MS. We review strategies that have been helpful for counting billions of protein molecules by LC-MS/MS and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome. We also examine the theoretical possibilities for scaling up single-molecule and mass-spectrometry proteomics approaches to quantifying the billions of protein molecules that make up the proteomes of our cells.
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportSupported dataset by repository
PrimarySubmitterDanielle Faivre
SpeciesList scientific name: Homo sapiens; NCBI TaxID: 9606;
InstrumentOrbitrap Eclipse
Dataset History
RevisionDatetimeStatusChangeLog Entry
02022-07-29 18:04:58ID requested
12022-08-01 14:35:00announced
22023-03-30 19:32:30announced: Added PubMed Id
Publication List
MacCoss MJ, Alfaro JA, Faivre DA, Wu CC, Wanunu M, Slavov N, Sampling the proteome by emerging single-molecule and mass spectrometry methods. Nat Methods, 20(3):339-346(2023) [pubmed]
Keyword List
submitter keyword: data independent acquisition, plasma, extracellular vesicles, bioinformatics
Contact List
Michael MacCoss
contact affiliationUniversity of Washington
contact emailmaccoss@uw.edu
lab head
Danielle Faivre
contact affiliationUniversity of Washington
contact emaildfaivre@uw.edu
dataset submitter
Full Dataset Link List
Panorama Public dataset URI