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PXD011574

PXD011574 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleMulti-parameter optimization of two common proteomics quantification methods for quantifying low-abundance proteins
DescriptionTo improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multi-parameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor co-isolation threshold, data analysis software, statistical calculation methods and protein fold changes. Five subprojects were included for this project.
HostingRepositoryiProX
AnnounceDate2018-11-02
AnnouncementXMLSubmission_2019-06-17_20:52:51.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterPiliang Hao
SpeciesList scientific name: Mus musculus; NCBI TaxID: 10090; scientific name: Homo sapiens; NCBI TaxID: 9606;
ModificationListiodoacetamide derivatized residue; deaminated residue; TMT6plex reporter fragment
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02018-11-04 19:12:18ID requested
12018-11-04 19:14:58announced
22019-06-17 20:33:20announcedUpdate publication information.
32019-06-17 20:52:52announcedUpdate publication information.
Publication List
Zhang C, Shi Z, Han Y, Ren Y, Hao P, Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins. J Proteome Res, 18(1):461-468(2019) [pubmed]
Keyword List
submitter keyword: quantitative proteomics, label-free quantification, tandem mass tags, low-abundance proteins, mass spectrometry
Contact List
Piliang Hao
contact affiliationShanghaiTech University
contact emailhaopl@shanghaitech.edu.cn
lab head
Piliang Hao
contact affiliationShanghaiTech University
contact emailhaopl@shanghaitech.edu.cn
dataset submitter
Full Dataset Link List
iProX dataset URI