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ProteomicsMultiplexed Quantitative Analyses Using Data-Dependent Acquisition Without Dynamic Exclusion for trace sample analysis
In this project, we applied our recently developed turboDDA method in the analysis of low amount of sample and iTRAQ labeled trace sample. Compared with standard data-ependent acquisition approach with dynamic exclusion, we detected improvment in spectral purity and quantification accuracy.
ORGANISM(S): Homo sapiens (Human) Escherichia coli Saccharomyces cerevisiae (Baker's yeast) 
2024-01-26 | PXD042252 | Pride
Turbodda Itraq 
ProteomicsBenchmarking turboDDA for Trace Sample Proteomics and Phosphoproteomics Analysis
In our previous work, a simple and robust approach termed turboDDA was reported to improve proteomics analysis in data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step on fast scanning time of flight (TOF) mass spectrometry (MS). However, its compatibility and potential on ...
ORGANISM(S): Homo Sapiens 
PXD073755 |
ProteomicsTrace sample analysis using Data-Dependent Acquisition Without Dynamic Exclusion
In this study, we report the application of turboDDA in improving trace sample analysis. Using different amount of K562 samples, we detected increases in identified protein number of more than 20% compared to all samples analyzed by standard DDA with dynamic exclusion.
ORGANISM(S): Homo sapiens (Human) 
2024-01-26 | PXD042385 | Pride
Turbodda K562 High ph fractionation De-dda 
UnknownTrace Sample Proteome Quantification by Data-Dependent Acquisition without Dynamic Exclusion.
Not available
S-EPMC10719888 | biostudies-literature
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