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ENA 2022 Poster 121

Systematic Evaluation of Label-Free Protein Quantification Pipelines (DDA vs DIA) in 12 Mouse Syngeneic Models

Binchen Mao, Kaijie Xiao, Xiaobo Chen, Jun Zhu, Hongbo Gu, Sheng Guo

Label-free proteomics quantification technology powered by LC-MS/MS is now routine to characterize and quantify thousands of proteins in tumor samples in a timely manner.

Data-dependent acquisition (DDA) has been the workhorse for bottom-up proteomics during the past few years. However, DDA suffers from a high percentage of missing data originating from its stochastic nature.

Due to this, data-independent acquisition (DIA) has gained increasing popularity in the field of bottom-up proteomics, due to higher reproducibility and improved data completeness.

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  • The side-by-side performance comparison between DDA and DIA in real studies

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