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MetabolomicsAutomated Label-free Quantification of Metabolites from Liquid Chromatography–Mass Spectrometry Data (Plasma)

Liquid chromatography coupled to mass spectrometry (LC-MS) has become a standard technology in metabolomics. In particular, label-free quantification based on LC-MS is easily amenable to large-scale studies and thus well suited to clinical metabolomics. Large-scale studies, however, require autom...

2015-12-16 | MTBLS234 | MetaboLights
MetabolomicsAutomated Label-free Quantification of Metabolites from Liquid Chromatography–Mass Spectrometry Data (Simulated)

Liquid chromatography coupled to mass spectrometry (LC-MS) has become a standard technology in metabolomics. In particular, label-free quantification based on LC-MS is easily amenable to large-scale studies and thus well suited to clinical metabolomics. Large-scale studies, however, require autom...

2015-12-16 | MTBLS235 | MetaboLights
ProteomicsMaxLFQ label-free quantification algorithm benchmark datasets
We developed a set of algorithms for label-free quantification, termed MaxLFQ, embedded into MaxQuant. This contains two datasets to benchmark MaxLFQ: The proteome benchmark dataset consists of of HeLa and E. coli lysates mixed at defined ratios. The dynamic range benchmark dataset consists of UPS1...
ORGANISM(S): Escherichia Coli (ncbitaxon:562) Homo Sapiens (ncbitaxon:9606) 
2017-12-19 | MSV000081831 | MassIVE
ProteomicsLFQbench enables a multi-centered benchmark study demonstrating robust proteomic label-free quantification
The consistent and accurate quantification of proteins is a challenging task for mass spectrometry (MS)-based proteomics. SWATH-MS uses data-independent acquisition (DIA) for label-free quantification. Here we evaluated five software tools for processing SWATH-MS data: OpenSWATH, SWATH2.0, Skyline, ...
ORGANISM(S): Escherichia Coli (ncbitaxon:562) Homo Sapiens (ncbitaxon:9606) Saccharomyces Cerevisiae (ncbitaxon:4932) 
2017-04-27 | MSV000081024 | MassIVE
ProteomicsSurfactant-assisted one-pot sample preparation for label-free single-cell proteomics
Large numbers of cells are generally required for quantitative global proteome profiling due to the significant surface adsorption losses associated with sample processing. Such bulk measurement obscures important cell-to-cell variability (cell heterogeneity) and makes proteomic profiling impossible...
ORGANISM(S): Homo Sapiens 
2021-03-11 | PXD022827 | panorama
ProteomicsA label-free shotgun proteomics analysis of macadamia nut
In this study, we present a first proteomic overview of macadamia nut using a label-free shotgun proteomic approach and prediction of their proteins with potential allergenic activity and cross-reactivity via an in silico analysis. The defense response proteins were the most abundant group of protei...
ORGANISM(S): Macadamia 
2020-01-13 | PXD015364 | Pride
Macadamia nut  label-free shotgun proteomics  in silico analysis  allergenicity  cross-reactivity 
ProteomicsCombining label-free and label-based accurate quantifications with SWATH-MS: comparison with SRM and PRM for the evaluation of bovine muscle type effects.
Mass spectrometry has proven to be a valuable tool for the accurate quantification of proteins. In this study, we have evaluated the performances of three targeted approaches, namely Selected Reaction Monitoring (SRM), Parallel Reaction Monitoring (PRM) and Sequential Windowed Acquisition of Theoret...
ORGANISM(S): Bos Taurus 
2021-06-08 | PXD020680 | panorama
ProteomicsProtein Biomarker Discovery for Methicillin-sensitive, Heterogeneous Vancomycin-Intermediate, and Vancomycin-intermediate Staphylococcus aureus Strains using Label-Free Data-Independent Acquisition Proteomics
90 S. aureus isolates were analyzed for protein biomarker discovery, including MSSA, vancomycin-susceptible S. aureus (VSSA), hVISA, and VISA strains. Label-free data-independent acquisition proteomics was used to identify protein biomarkers that allow for discrimination among MSSA, hVISA, and VISA ...
ORGANISM(S): Staphylococcus Aureus (ncbitaxon:1280) 
2020-07-18 | MSV000085776 | MassIVE
ProteomicsLabel-free quantification in ion-mobility enhanced data-independent acquisition proteomics
Data-dependent acquisition (DDA) methods are a well-established tool for proteome analysis and have greatly expedited the field of shotgun proteomics. However, their serial and stochastic nature restricts their reproducibility and limits the detectable dynamic range to the peptides that ionize best....
ORGANISM(S): Homo sapiens (Human) Saccharomyces cerevisiae (strain Lalvin EC1118 / Prise de mousse) (Baker's yeast) Escherichia coli 
2016-03-29 | PXD002393 | Pride
Proteomics Mass spectrometry Label-free quantification Ion mobility separation Data-independent acquisition 
ProteomicsRobust collection and processing for label-free single voxel proteomics
With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures important tissue heterogeneity, which make it impossible for proteome mapping of tissue microenvironment. Here...
ORGANISM(S): Homo Sapiens (human) 
2024-11-01 | PXD045043 | JPOST Repository
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