Daryl Wilding-McBride is an author of research on computational analysis of mass spectrometry data. A 2022 paper with collaborators developed processing methods for precursor and fragment spectra acquired on a timsTOF instrument, with the aim of improving peptide feature characterization and identification.[ref]
One useful contribution concerns detector saturation. Strong isotopic peaks can cease to represent their true relative intensities. The paper uses a theoretical model of tryptic-peptide peak-height ratios and an unsaturated later isotope to infer earlier peak intensities, including the monoisotopic peak. This is model-based reconstruction, not a second direct measurement of a saturated signal.[ref]
Simplifying MS1 and MS2 spectra to achieve lower mass error, more dynamic range, and higher peptide identification confidence on the Bruker timsTOF Pro by Daryl Wilding-McBride and others. §3.3, Correcting intensity readings in saturation; Figures7–10
For an original calculation illustrating the inference, suppose a declared model predicts and an unsaturated later peak has intensity arbitrary units. The inferred earlier intensity is units. The arithmetic is straightforward; whether it is informative depends on the appropriateness of the isotope-ratio model and the reliability of the unsaturated measurement.
The paper evaluates such processing in defined proteomic mixtures. Its detector threshold and applicable isotope/mass ranges belong to that data-processing setup, rather than constituting universal limits for every mass spectrometer. The example illustrates how a software correction can recover a useful estimate while retaining dependence on its physical and statistical assumptions.[ref]
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