Journal of Chemical Information and Modeling · 2019 · 18 citations · 18 references
EngineeringData ExplorationSpectrochemical AnalysisPhenomicsData ScienceScientific Data ManagementAnalytical ChemistryBiostatisticsProteomicsMass Spectrometric DataPythoms FrameworkBiochemistryOmicsMetabolomicsComputational Mass SpectrometryBioinformaticsBiologyPython FrameworkPython Programming LanguageOmics DatasetsScientific VisualizationMass SpectrometryComputational BiologySpectral SearchingSystems BiologyMedicine
Mass spectrometric data are copious and generate a processing burden that is best dealt with programmatically. PythoMS is a collection of tools based on the Python programming language that assist researchers in creating figures and video output that is informative, clear, and visually compelling. The PythoMS framework introduces a library of classes and a variety of scripts that quickly perform time-consuming tasks: making proprietary output readable; binning intensity vs time data to simulate longer scan times (and hence reduce noise); calculating theoretical isotope patterns and overlaying them in histogram form on experimental data (an approach that works even for overlapping signals); rendering videos that enable zooming into the baseline of intensity vs time plots (useful to make sense of data collected over a large dynamic range) or that depict the evolution of different species in a time-lapse format; calculating aggregates; and providing a quick first-pass at identifying fragments in MS/MS spectra. PythoMS is a living project that will continue to evolve as additional scripts are developed and deployed.
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ProteoWizard: open source software for rapid proteomics tools development
Darren Kessner, Matt Chambers, Robert Burke et al. · Bioinformatics · 2008 · 2K citations · Full text
mzML—a Community Standard for Mass Spectrometry Data
Lennart Martens, Matthew Chambers, Marc Sturm et al. · Molecular & Cellular Proteomics · 2010 · 774 citations · Full text
Anton Goloborodko, Lev I. Levitsky, Mark V. Ivanov et al. · Journal of the American Society for Mass Spectrometry · 2013 · 224 citations · Full text
Molecular Biology, Sequence Parsing, Proteomic Technology +18