PRECURSOR SELECTION USING AN ARTIFICIAL INTELLIGENCE ALGORITHM INCREASES PROTEOMIC SAMPLE COVERAGE AND REPRODUCIBILITY

Described herein are mass spectrometry systems and methods which utilize a dynamic a new data acquisition/instrument control methodology. These systems and methods employ novel artificial intelligence algorithms to greatly increase quantitative and/or identification accuracy during data acquisition. In an embodiment, the algorithms can adapt the instrument methods and systems during data acquisition to direct data acquisition resources to increase quantitative or identification accuracy of target analytes, such as proteins, peptides, and peptide fragments.