Ryan T. Fellers

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With the prospect of resolving whole protein molecules into their myriad proteoforms on a proteomic scale, the question of their quantitative analysis in discovery mode comes to the fore. Here, we demonstrate a robust pipeline for the identification and stringent scoring of abundance changes of whole protein forms <30 kDa in a complex system. The input is(More)
The automated processing of data generated by top down proteomics would benefit from improved scoring for protein identification and characterization of highly related protein forms (proteoforms). Here we propose the "C-score" (short for Characterization Score), a Bayesian approach to the proteoform identification and characterization problem, implemented(More)
Efforts to map the human protein interactome have resulted in information about thousands of multi-protein assemblies housed in public repositories, but the molecular characterization and stoichiometry of their protein subunits remains largely unknown. Here, we report a computational search strategy that supports hierarchical top-down analysis for precise(More)
The ability to study organisms by direct analysis of their proteomes without digestion via mass spectrometry has benefited greatly from recent advances in separation techniques, instrumentation, and bioinformatics. However, improvements to data acquisition logic have lagged in comparison. Past workflows for Top Down Proteomics (TDPs) have focused on high(More)
Intact protein characterization using mass spectrometry thus far has been achieved at the cost of throughput. Presented here is the application of 193 nm ultraviolet photodissociation (UVPD) for top down identification and characterization of proteins in complex mixtures in an online fashion. Liquid chromatographic separation at the intact protein level(More)
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