ArticleJournal of the American Society for Mass Spectrometry2017
Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry.
Article in Journal of the American Society for Mass Spectrometry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A Multi-Parameter Persistence Algorithm for the Automatic Energy Calibration of Scintillating Radiation Sensors.Sensors (Basel, Switzerland) · 2025Article
- Multimodal Mass Spectrometry Imaging in Atlas Building: A Review.Seminars in nephrology · 2024Review
- NECTAR: A New Algorithm for Characterizing and Correcting Noise in QToF-Mass Spectrometry Imaging Data.Journal of the American Society for Mass Spectrometry · 2023Article
- Determining the Location of the α-Synuclein Dimer Interface Using Native Top-Down Fragmentation and Isotope Depletion-Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2023Article
- Peak learning of mass spectrometry imaging data using artificial neural networks.Nature communications · 2021Article
- Evaluation of Sibling and Twin Fragment Ions Improves the Structural Characterization of Proteins by Top-Down MALDI In-Source Decay Mass Spectrometry.Analytical chemistry · 2020Article
- Top or Middle? Up or Down? Toward a Standard Lexicon for Protein Top-Down and Allied Mass Spectrometry Approaches.Journal of the American Society for Mass Spectrometry · 2019Article
- Top Down Tandem Mass Spectrometric Analysis of a Chemically Modified Rough-Type Lipopolysaccharide Vaccine Candidate.Journal of the American Society for Mass Spectrometry · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. Graphical Abstract ᅟ.
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27924495What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.