Speaker: Jérémy Potriquet, Field Application Specialist, SCIEX Oceania
In recent years the speed and sensitivity of proteomic data collection and speed of processing have been steadily increasing. It is reaching the zenith of producing the quantities of data needed for the efficient training of deep learning models and unlocking the full potential of machine learning in the prediction of peptide properties, retention time, peak detection, and identification. Recent studies and observations are giving more and more confidence that increasing the rate of analysis has a limited impact on the quality of the data with the peptide-centric approach and is now creating a paradigm shift in the way we perceive and operate proteomics experiments. In this workshop, we will discuss what are the characteristics and advantages of running a fast proteomic analysis and the opportunities that it is leading to for the future of proteomics applications.