On the public citation graph

A Data Set of 255,000 Randomly Selected and Manually Classified Extracted Ion Chromatograms for Evaluation of Peak Detection Methods

https://doi.org/10.3390/metabo10040162
0 signed · 30 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00216-015-8681-7openalex-snapshot
Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis
inferredcites →https://doi.org/10.1007/s00216-016-9919-8openalex-snapshot
Optimization of LC-Orbitrap-HRMS acquisition and MZmine 2 data processing for nontarget screening of environmental samples using design of experiments
inferredcites →https://doi.org/10.1016/j.scitotenv.2020.138388openalex-snapshot
Unraveling longitudinal pollution patterns of organic micropollutants in a river by non-target screening and cluster analysis
inferredcites →https://doi.org/10.1021/ac051437yopenalex-snapshot
XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification
inferredcites →https://doi.org/10.1021/ac301482kopenalex-snapshot
Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach
inferredcites →https://doi.org/10.1186/1471-2105-11-395openalex-snapshot
MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
inferredcites →https://doi.org/10.1186/1471-2105-9-375openalex-snapshot
Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements
inferredcites →https://doi.org/10.1186/s12859-015-0562-8openalex-snapshot
IPO: a tool for automated optimization of XCMS parameters

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← backgroundhttps://doi.org/10.5281/zenodo.3756211zenodo-depositor-declared
inferred← citeshttps://doi.org/10.1002/cbdv.202100272openalex-snapshot
Acetylated Rhamnose Triterpenoid Saponins from Glechoma longituba Analyzed by LC‐Q‐TOFMS
inferred← citeshttps://doi.org/10.1016/j.chemolab.2022.104694openalex-snapshot
Deep denoising autoencoder-assisted continuous scoring of peak quality in high-resolution LC−MS data
inferred← citeshttps://doi.org/10.1016/j.trac.2024.117674openalex-snapshot
Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis
inferred← citeshttps://doi.org/10.1016/j.trac.2026.118964openalex-snapshot
Processing of non-targeted LC-HRMS data: Progress and challenges in automated data-driven optimisations
inferred← citeshttps://doi.org/10.1021/acs.analchem.0c00899openalex-snapshot
Symbolic Aggregate Approximation Improves Gap Filling in High-Resolution Mass Spectrometry Data Processing
inferred← citeshttps://doi.org/10.1021/acs.analchem.0c04698openalex-snapshot
Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics─Standardization, Coverage, and Throughput
inferred← citeshttps://doi.org/10.1021/acs.analchem.1c05270openalex-snapshot
Power of mzRAPP-Based Performance Assessments in MS1-Based Nontargeted Feature Detection
inferred← citeshttps://doi.org/10.1039/d1ay00111fopenalex-snapshot
Suspect and non-target screening: the last frontier in environmental analysis
inferred← citeshttps://doi.org/10.1093/bioinformatics/btad195openalex-snapshot
3D-MSNet: a point cloud-based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data
inferred← citeshttps://doi.org/10.1101/2021.09.09.459600openalex-snapshot
Benchmarking feature quality assurance strategies for non-targeted metabolomics
inferred← citeshttps://doi.org/10.1186/s12302-020-00415-5openalex-snapshot
Non-target screening for detecting the occurrence of plant metabolites in river waters
inferred← citeshttps://doi.org/10.1186/s12302-021-00464-4openalex-snapshot
Occurrence of plant secondary metabolite fingerprints in river waters from Eastern Jutland, Denmark
inferred← citeshttps://doi.org/10.1186/s12859-023-05533-4openalex-snapshot
Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
inferred← citeshttps://doi.org/10.14233/ajchem.2025.33771openalex-snapshot
Isolation of Chemical Compounds of Astragalus galactites from Mongolia
inferred← citeshttps://doi.org/10.21248/gups.61018openalex-snapshot
Analytical screening for possibly toxic plant secondary metabolites in surface waters by liquid chromatography coupled to high resolution mass spectrometry
inferred← citeshttps://doi.org/10.6084/m9.figshare.13049150openalex-snapshot
Additional file 2 of Non-target screening for detecting the occurrence of plant metabolites in river waters
inferred← citeshttps://doi.org/10.6084/m9.figshare.24452498openalex-snapshot
Additional file 1 of Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
inferred← citeshttps://doi.org/10.6084/m9.figshare.24452643openalex-snapshot
Additional file 2 of Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
inferred← citeshttps://doi.org/10.6084/m9.figshare.26633475openalex-snapshot
Additional file 3 of Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
inferred← citeshttps://doi.org/10.6084/m9.figshare.26633478openalex-snapshot
Additional file 4 of Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
inferred← citeshttps://doi.org/10.6084/m9.figshare.26633481openalex-snapshot
Additional file 5 of Picky with peakpicking: assessing chromatographic peak quality with simple metrics in metabolomics
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.