ArticleJournal of proteome research2012
Evaluation of database search programs for accurate detection of neuropeptides in tandem mass spectrometry experiments.
Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Limitations of Mass Spectrometry-Based Peptidomic Approaches.Journal of the American Society for Mass Spectrometry · 2015Pooled it
- Decoding Neuropeptide Complexity: Advancing Neurobiological Insights from Invertebrates to Vertebrates through Evolutionary Perspectives.ACS chemical neuroscience · 2025Review
- EndoGenius: Optimized Neuropeptide Identification from Mass Spectrometry Datasets.Journal of proteome research · 2024Article
- A crustacean neuropeptide spectral library for data-independent acquisition (DIA) mass spectrometry applications.Proteomics · 2024Article
- Origins, Technological Advancement, and Applications of Peptidomics.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Recent advances in mass spectrometry analysis of neuropeptides.Mass spectrometry reviews · 2023Review
- HyPep: An Open-Source Software for Identification and Discovery of Neuropeptides Using Sequence Homology Search.Journal of proteome research · 2023Article
- The language of proteins: NLP, machine learning & protein sequences.Computational and structural biotechnology journal · 2021Review
- Differential Transcriptome Networks between IDO1-Knockout and Wild-Type Mice in Brain Microglia and Macrophages.PloS one · 2016Article
- Peptidomics for the discovery and characterization of neuropeptides and hormones.Trends in pharmacological sciences · 2015Review
- Identification of best indicators of peptide-spectrum match using a permutation resampling approach.Journal of bioinformatics and computational biology · 2014Article
- Comparing label-free quantitative peptidomics approaches to characterize diurnal variation of peptides in the rat suprachiasmatic nucleus.Analytical chemistry · 2014Article
- Accurate assignment of significance to neuropeptide identifications using Monte Carlo k-permuted decoy databases.PloS one · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Neuropeptide identification in mass spectrometry experiments using database search programs developed for proteins is challenging. Unlike proteins, the detection of the complete sequence using a single spectrum is required to identify neuropeptides or prohormone peptides. This study compared the performance of three open-source programs used to identify proteins, OMSSA, X!Tandem and Crux, to identify prohormone peptides. From a target database of 7850 prohormone peptides, 23550 query spectra were simulated across different scenarios. Crux was the only program that correctly matched all peptides regardless of p-value and at p-value<1×10(-2), 33%, 64%, and >75%, of the 5, 6, and ≥7 amino acid-peptides were detected. Crux also had the best performance in the identification of peptides from chimera spectra and in a variety of missing ion scenarios. OMSSA, X!Tandem and Crux correctly detected 98.9% (99.9%), 93.9% (97.4%) and 88.7% (98.3%) of the peptides at E- or p-value<1×10(-6) (<1×10(-2)), respectively. OMSSA and X!Tandem outperformed the other programs in significance level and computational speed, respectively. A consensus approach is not recommended because some prohormone peptides were only identified by one program.
Indexed as
Identifiers
What 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.