Browsing by Subject "bottom-up proteomics"

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    De Novo Sequencing of Peptides from High-Resolution Bottom-Up Tandem Mass Spectra using Top-Down Intended Methods
    (Wiley, 2017-12) Vyatkina, Kira; Dekker, Lennard J. M.; Wu, Si; VanDuijn, Martijn M.; Liu, Xiaowen; Tolić, Nikola; Luider, Theo M.; Paša-Tolić, Ljiljana; BioHealth Informatics, School of Informatics and Computing
    Despite high-resolution mass spectrometers are becoming accessible for more and more laboratories, tandem (MS/MS) mass spectra are still often collected at a low resolution. And even if acquired at a high resolution, software tools used for their processing do not tend to benefit from that in full, and an ability to specify a relative mass tolerance in this case often remains the only feature the respective algorithms take advantage of. We argue that a more efficient way to analyze high-resolution MS/MS spectra should be with methods more explicitly accounting for the precision level, and sustain this claim through demonstrating that a de novo sequencing framework originally developed for (high-resolution) top-down MS/MS data is perfectly suitable for processing high-resolution bottom-up datasets, even though a top-down like deconvolution performed as the first step will leave in many spectra at most a few peaks.