Data Processing and Machine Learning Methods to Analyze MALDI-TOF MS Data

MALDI-TOF MS is a rapid, sensitive method for generating complex protein profiles from minimal sample volumes. Although its spectra lack direct peptide sequence information, combining MALDI-TOF output with machine learning enables discrimination of diseases based on intensity patterns. Accurate machine learning model development depends on standardized preprocessing to reduce noise, dimensionality, and bias. This protocol demonstrates two key preprocessing approaches-peak picking and spectral binning-and demonstrates their application in training and testing a machine learning model for the diagnosis of glioblastoma.