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ProteomicsDetergent Screening with Hybrid Detergents Increases Observable Number of Protein Identities in Bottom-Up Proteomics
Detergents are key reagents in bottom-up proteomics that create an apparent, yet underappreciated bias on observable proteomes. Maximizing the chemical diversity in parallelized detergent screens is supposed to maximize observable proteomes by combining proteomics data sets of different detergents. ...
ORGANISM(S): Escherichia coli 
2025-08-25 | PXD060875 | Pride
Proteomics E. coli Bottum-up Hybrid detergent Sds 
ProteomicsA comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics
A comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics using SCIEX TripleTOF5600 and 6600+, Orbitrap QE-HFX, Waters Synapt GS-Si and Synapt XS and Bruker timsTOF Pro.
ORGANISM(S): Candida albicans (Yeast) Homo sapiens (Human) Escherichia coli 
2022-02-14 | PXD028735 | Pride
Swath Dia Benchmark 
ProteomicsHybrid QconCAT-based Targeted Absolute and Data-independent Acquisition-based Label-free Quantification Enables In-depth Proteomic Characterization of Wheat ATI Extracts
In this study, we present a novel hybrid data-independent acquisition LC-MS approach, combining QconCAT technology with short microflow LC gradients and DIA and apply the method towards the quantitative proteome analysis of ATI extracts from wheat flour. The novel method is fast, robust and reproduc...
ORGANISM(S): Triticum aestivum (Wheat) 
2021-04-22 | PXD021381 | Pride
Wheat Dia Data-independent acquisition Qconcat Absolute quantification Microflow lc-ms Ati Triticum Amylase-trypsin inhibitor 
ProteomicsMachine Learning Based Classification of Diffuse Large B-cell Lymphoma Patients by their Protein Expression Profiles
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we ...
ORGANISM(S): Homo sapiens (Human) 
2015-09-08 | PXD002052 | Pride
Classification Proteomics Svm Lymphoma Hybrid lfq 
ProteomicsMachine Learning Based Classification of Diffuse Large B-cell Lymphoma Patients by their Protein Expression Profiles
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we ...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
2017-03-30 | MSV000080813 | MassIVE
UnknownA comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics.
Not available
S-EPMC8967878 | biostudies-literature
ProteomicsHybrid Epithelial-Mesenchymal status of lung cancer dictates metastatic success through differential interaction with NK cells
Background Epithelial to mesenchymal transition (EMT) endows cancer cells with pro-metastatic properties, which appear most effective when cells enter an intermediate hybrid (H) state, characterized by integrated mesenchymal (M) and epithelial (E) traits. The reasons for this advantage are poorly kn...
ORGANISM(S): Homo sapiens (Human) 
2024-05-21 | PXD044297 | Pride
Cancer initiating cell Proteomics Mass spectrometry Natural killer Epithelial-to-mesenchymal transition 
UnknownComprehensive Single-Shot Proteomics with FAIMS on a Hybrid Orbitrap Mass Spectrometer.
Not available
S-EPMC6145172 | biostudies-literature
ProteomicsNanobody-thioesterase chimeras to specifically target protein palmitoylation
Global (TMT) proteome and palmitoylated (LFQ) proteome after expression of APT2-LAMA-G97. The detailed methodology and results are available in the manuscript Nanobody-thioesterase chimeras to specifically target protein palmitoylation
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
2024-11-07 | MSV000096329 | MassIVE
OtherMachine Learning Based Classification of Diffuse Large B-cell Lymphoma Patients by their Protein Expression Profiles.
Data from ProteomeXchange, PXD ID: PXD002052. Experiment: TRR37, file: folder summary. Published as part of Mol Cell Proteomics. 2015 Aug 26 . From the Abstract: {{i}} ... Here, we develop a state of the art quantitative mass spectrometric pipeline to characterize formalin-fixed paraffin-embedded (...
ORGANISM(S): Homo_sapiens_viruses, Human 
GPM32320017943 | GPMDB
Resource Reanalysis 
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