ArticleJournal of proteome research2013
Evaluation and optimization of mass spectrometric settings during data-dependent acquisition mode: focus on LTQ-Orbitrap mass analyzers.
Article in Journal of proteome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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
53 citing papers in PubMed.
- Detecting and Grouping In-Source Fragments with Low-Energy Stepped HCD, Together with MSMetabolites · 2026Article
- Mass spectrometry-based proteomics of FFPE tissues: progress, limitations, and clinical translation barriers.Clinical proteomics · 2025Review
- Identification of Protein Networks and Biological Pathways Driving the Progression of Atherosclerosis in Human Carotid Arteries Through Mass Spectrometry-Based Proteomics.International journal of molecular sciences · 2024Article
- Proteomes of plasmodium knowlesi early and late ring-stage parasites and infected host erythrocytes.Journal of proteomics · 2024Article
- An Enzymatic and Proteomic Analysis ofJournal of fungi (Basel, Switzerland) · 2024Article
- A planar quadrupole device for transmitting and trapping ions in high vacuum.Rapid communications in mass spectrometry : RCM · 2023Article
- Optimization of Mass Spectrometric Parameters in Data Dependent Acquisition for Untargeted Metabolomics on the Basis of Putative Assignments.Journal of the American Society for Mass Spectrometry · 2023Article
- DiffN Selection of Tandem Mass Spectrometry Precursors.Analytical chemistry · 2023Article
- Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses.Journal of the American Society for Mass Spectrometry · 2023Article
- Proteomic Insights of Cowpea Response to Combined Biotic and Abiotic Stresses.Plants (Basel, Switzerland) · 2023Article
- Definitive Screening Designs to Optimize Library-Free DIA-MS Identification and Quantification of Neuropeptides.Journal of proteome research · 2023Article
- A Highly Efficient Workflow for Detecting and Identifying Sequence Variants in Therapeutic Proteins with a High Resolution LC-MS/MS Method.Molecules (Basel, Switzerland) · 2023Article
- Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics.Mass spectrometry reviews · 2023Review
- Non-target molecular network and putative genes of flavonoid biosynthesis inFrontiers in plant science · 2022Article
- Identification of alkaloids and related intermediates ofFrontiers in plant science · 2022Article
- Human metabolism and urinary excretion of seven neonicotinoids and neonicotinoid-like compounds after controlled oral dosages.Archives of toxicology · 2022Article
- Mass Spectrometric Profiling of Neuropeptides in Response to Copper Toxicity via Isobaric Tagging.Chemical research in toxicology · 2021Article
- Identification of lipidomic profiles associated with drug-resistant prostate cancer cells.Lipids in health and disease · 2021Article
- Biological Applications for LC-MS-Based Proteomics.Advances in experimental medicine and biology · 2021Article
- Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale.Frontiers in bioinformatics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Mass-spectrometry-based proteomics has evolved as the preferred method for the analysis of complex proteomes. Undoubtedly, recent advances in mass spectrometry instrumentation have greatly enhanced proteomic analysis. A popular instrument platform in proteomics research is the LTQ-Orbitrap mass analyzer. In this tutorial, we discuss the significance of evaluating and optimizing mass spectrometric settings on the LTQ-Orbitrap during CID data-dependent acquisition (DDA) mode to improve protein and peptide identification rates. We focus on those MS and MS/MS parameters that have been systematically examined and evaluated by several researchers and are commonly used during DDA. More specifically, we discuss the effect of mass resolving power, preview mode for FTMS scan, monoisotopic precursor selection, signal threshold for triggering MS/MS events, number of microscans per MS/MS scan, number of MS/MS events, automatic gain control target value (ion population) for MS and MS/MS, maximum ion injection time for MS/MS, rapid and normal scan rate, and prediction of ion injection time. We furthermore present data from the latest generation LTQ-Orbitrap system, the Orbitrap Elite, along with recommended MS and MS/MS parameters. The Orbitrap Elite outperforms the Orbitrap Classic in terms of scan speed, sensitivity, dynamic range, and resolving power and results in higher identification rates. Several of the optimized MS parameters determined on the LTQ-Orbitrap Classic and XL were easily transferable to the Orbitrap Elite, whereas others needed to be reevaluated. Finally, the Q Exactive and HCD are briefly discussed, as well as sample preparation, LC-optimization, and bioinformatics analysis. We hope this tutorial will serve as guidance for researchers new to the field of proteomics and assist in achieving optimal results.
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.