= Daryl Wilding-McBride
{c}
\b[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.<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>[Title, author byline, Abstract and algorithm overview]{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.<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]{ref}
For an original calculation illustrating the inference, suppose a declared model predicts $I_0/I_j=2.5$ and an unsaturated later peak has intensity $I_j=400$ arbitrary units. The inferred earlier intensity is $\widehat I_0=2.5\times400=1000$ 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.<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, model range and mixture comparisons]{ref}
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