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• W2330976336 abstract "The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets." @default.
• W2330976336 created "2016-06-24" @default.
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• W2330976336 date "2013-10-03" @default.
• W2330976336 modified "2023-10-14" @default.
• W2330976336 title "Mspire-Simulator: LC-MS Shotgun Proteomic Simulator for Creating Realistic Gold Standard Data" @default.
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• W2330976336 doi "https://doi.org/10.1021/pr400727e" @default.
• W2330976336 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24090032" @default.
• W2330976336 hasPublicationYear "2013" @default.
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