PNNL

Abstract

The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) holds the potential to revolutionize the MS field in unprecedented ways. Grounded in computational MS, this perspective article delves into the various facets of this transformation, enumerating current challenges, opportunities, and expectable improvements. From metadata collection to raw data processing, molecular annotation, multiomics integration with biological interpretation, and towards enabling autonomous experiments, various areas of how AI can advance MS and its applications are summarized. This personal perspective provides an overview of how AI is poised to reshape the future of MS, improving efficiency, accuracy, molecular breadth of coverage, holistic data interpretation, and ultimately biological insight.