Systems and methods of ion population regulation in mass spectrometry

Abstract

A computer-implemented method of training a machine learning model comprises: accessing an elution profile comprising a plurality of detection points representing intensity of ions derived from components eluting from a chromatography column and detected by a mass analyzer as a function of time; generating, based on the elution profile, training data comprising a plurality of training examples, a training example of the plurality of training examples comprising a set of detection points and a target next detection point, the target next detection point comprising a detection point of the plurality of detection points following the set of detection points; and training, using the training data, the machine learning model to determine a predicted next detection point, the predicted next detection point following the set of detection points.

Dependencies are inferred from the claim text.