ArticleBMC genomics2014
Spectral probabilities of top-down tandem mass spectra.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- The Open Pediatric Cancer Project.bioRxiv : the preprint server for biology · 2025Article
- The Open Pediatric Cancer Project.GigaScience · 2025Article
- SPECTRUM - A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data.Scientific reports · 2019Article
- Review
- A Markov Chain Monte Carlo Method for Estimating the Statistical Significance of Proteoform Identifications by Top-Down Mass Spectrometry.Journal of proteome research · 2019Article
- Systematic Evaluation of Protein Sequence Filtering Algorithms for Proteoform Identification Using Top-Down Mass Spectrometry.Proteomics · 2018Article
- Myofibrillar Z-discs Are a Protein Phosphorylation Hot Spot with Protein Kinase C (PKCα) Modulating Protein Dynamics.Molecular & cellular proteomics : MCP · 2017Article
- TopPIC: a software tool for top-down mass spectrometry-based proteoform identification and characterization.Bioinformatics (Oxford, England) · 2016Article
- SpectroGene: A Tool for Proteogenomic Annotations Using Top-Down Spectra.Journal of proteome research · 2016Article
- MS-GF+ makes progress towards a universal database search tool for proteomics.Nature communications · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn mass spectrometry-based proteomics, the statistical significance of a peptide-spectrum or protein-spectrum match is an important indicator of the correctness of the peptide or protein identification. In bottom-up mass spectrometry, probabilistic models, such as the generating function method, have been successfully applied to compute the statistical significance of peptide-spectrum matches for short peptides containing no post-translational modifications. As top-down mass spectrometry, which often identifies intact proteins with post-translational modifications, becomes available in many laboratories, the estimation of statistical significance of top-down protein identification results has come into great demand.
resultsIn this paper, we study an extended generating function method for accurately computing the statistical significance of protein-spectrum matches with post-translational modifications. Experiments show that the extended generating function method achieves high accuracy in computing spectral probabilities and false discovery rates.
conclusionsThe extended generating function method is a non-trivial extension of the generating function method for bottom-up mass spectrometry. It can be used to choose the correct protein-spectrum match from several candidate protein-spectrum matches for a spectrum, as well as separate correct protein-spectrum matches from incorrect ones identified from a large number of tandem mass spectra.
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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.