Evidence map›Paper›PMID 40055306›Full record

ArticleNature communications2025

FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events.

Yannek Nowatzky, Francesco Friedrich Russo, Jan Lisec, Alexander Kister, Knut Reinert, Thilo Muth, Philipp Benner

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yannek NowatzkySection VP.1 eScience, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany.ORCID http://orcid.org/0000-0001-7537-3694
Francesco Friedrich RussoDepartment of Analytical Chemistry and Reference Materials, Organic Trace Analysis and Food Analysis, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany.
Jan LisecDepartment of Analytical Chemistry and Reference Materials, Organic Trace Analysis and Food Analysis, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany.ORCID http://orcid.org/0000-0003-1220-2286
Alexander KisterSection VP.1 eScience, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany.
Knut ReinertDepartment of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.ORCID http://orcid.org/0000-0003-3078-8129
Thilo MuthDepartment of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.ORCID http://orcid.org/0000-0001-8304-2684
Philipp BennerSection VP.1 eScience, Federal Institute for Materials Research and Testing (BAM), Berlin, Germany. philipp.benner@bam.de.ORCID http://orcid.org/0000-0002-0912-8137

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging task due to the incomplete nature of spectral reference libraries. Augmenting these libraries with simulated mass spectra can provide the necessary references to resolve unmatched spectra, but generating high-quality data is difficult. In this study, we present FIORA, an open-source graph neural network designed to simulate tandem mass spectra. Our main contribution lies in utilizing the molecular neighborhood of bonds to learn breaking patterns and derive fragment ion probabilities. FIORA not only surpasses state-of-the-art fragmentation algorithms, ICEBERG and CFM-ID, in prediction quality, but also facilitates the prediction of additional features, such as retention time and collision cross section. Utilizing GPU acceleration, FIORA enables rapid validation of putative compound annotations and large-scale expansion of spectral reference libraries with high-quality predictions.

Indexed as

MetabolomicsNeural Networks, ComputerTandem Mass SpectrometryAlgorithmsSoftware

Identifiers

PMID40055306
PMCPMC11889238

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Registered trials

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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.