IMSC: Improvements in LFQ for reproducible quantification of proteomic experiments: how DDA outperform DIA

Poster Note 64785 Improvements in LFQ for reproducible quantification of proteomic experiments: how DDA outperforms DIA Improvements in LFQ for reproducible quantification Ignacio Ortea1, Romain Huguet2, David Horn2, Andreas FR Huhmer2, and Daniel Lopez-Ferrer2 IMIBIC, Cordoba, Spain, 2 Thermo Fisher…

Optimized DDA+ and HR-DIA workflows for standardized, reproducible, precise and robust label-free quantitation of proteomes Aaron S. Gajadhar1, Oleksandr Boychenko2, Xin Zhang3, Yue Xuan4, and Andreas Huhmer1, Thermo Fisher Scientific, San Jose1, CA, USA; Germering, Germany2; Sunnyvale, CA3, USA; Bremen,…

2017 Metabolomics Seminars Pushing the Leading Edge in Protein Quantitation: Integrated, Precise, and Reproducible Protein Quantitation Workflow Solutions The world leader in serving science 2 3 Cancer Moonshot Goal: To detect cancer at an early stage while providing additional therapies…

APPLICATION NOTE 21744 Robust LC Separation Optimized MS Acquisition Comprehensive Data Informatics A highly sensitive and robust 150 µm column to enable high-throughput proteomics Authors Xin Zhang, Aaron Gajadhar, Xuefei Sun,1 Mike Baynham3 1 Thermo Fisher Scientific, Sunnyvale, CA, USA…