ArticleAnalytical chemistry2019
Accelerating Lipidomic Method Development through
Article in Analytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Deep Learning Predicts Non-Normal Transmission Distributions in High-Field Asymmetric Waveform Ion Mobility (FAIMS) Directly from Peptide Sequence.Analytical chemistry · 2025Article
- LC-ESI-HRMS - lipidomics of phospholipids : Characterization of extraction, chromatography and detection parameters.Analytical and bioanalytical chemistry · 2024Article
- Simulation of mass spectrometry-based proteomics data with Synthedia.Bioinformatics advances · 2023Article
- Data Processing of Product Ion Spectra: Redundancy of Product Ion Spectra of Small Molecules in Data-Dependent Acquisition Dataset.Mass spectrometry (Tokyo, Japan) · 2023Article
- Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules.Mass spectrometry (Tokyo, Japan) · 2022Article
- The role of lipids in exosome biology and intercellular communication: Function, analytics and applications.Traffic (Copenhagen, Denmark) · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing suboptimal results. Here we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the
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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.