Evidence map›Paper›PMID 41328747›Full record

ArticleJournal of the American Society for Mass Spectrometry2026

Multiple Spectrum Alignment for Molecular Networking Exploration and Discovery.

Amy Lau, Xianghu Wang, Tao Xu, Tilman Schramm, Yasin El Abiead, Daniel Petras, Vanessa V Phelan, Mingxun Wang

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Amy LauDepartment of Statistics, University of California Riverside, , 900 University Ave, Riverside, California 92521, United States.
Xianghu WangDepartment of Computer Science and Engineering, University of California Riverside, , 900 University Ave, Riverside, California 92521, United States.
Tao XuDepartment of Computer Science and Engineering, University of California Riverside, , 900 University Ave, Riverside, California 92521, United States.
Tilman SchrammDepartment of Biochemistry, University of California Riverside, 900 University Ave, Riverside, California 92521, United States.
Yasin El AbieadSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, San Diego, California 92093-0751, United States.
Daniel PetrasDepartment of Biochemistry, University of California Riverside, 900 University Ave, Riverside, California 92521, United States.
Vanessa V PhelanDepartment of Pharmaceutical Sciences, University of Colorado, Anschutz Medical Campus, 12850 E Montview Blvd, Aurora, Colorado 80045, United States.ORCID 0000-0001-7156-9294
Mingxun WangDepartment of Computer Science and Engineering, University of California Riverside, , 900 University Ave, Riverside, California 92521, United States.ORCID 0000-0001-7647-6097

Funding

Collaborative Microbial Metabolite CenterU24DK133658 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PIETER C DORRESTEIN · 2022 to 2026
$2.9M
Characterizing Natural Product Mediated Microbial InteractionsR35GM158024 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI Vanessa V Phelan · 2025 to 2026
$846k
NIDDK NIH HHS U24 DK133658NIGMS NIH HHS R35 GM158024
6 · The paper itself

Abstract

Molecular networking is a computational mass spectrometry technique used to visualize and connect tandem mass spectra from putatively related molecules to reveal structural relationships. Despite their utility, existing tools for interpreting molecular networks are limited in the ability to easily organize fragmentation patterns within molecular families. We developed an interactive web-based tool, the Multiple Mass Spectral Alignment (MMSA) approach, that enhances the visualization of molecular networks by displaying detailed spectral alignment information among all the spectra in a network component in one visualization. MMSA identifies sets of consensus peaks that contribute to the alignment of multiple tandem mass spectra, offering insights into how structural moieties captured by specific fragments influence the construction of molecular networks. We demonstrate that MMSA facilitates insightful understanding of molecular networks and improves the interpretability of the tandem mass spectra, capturing the chemical modifications or core structures within a molecular family. We envision that the MMSA tool will significantly enhance the ability to interpret molecular networks, with implications for more rapid identification and prioritization of new metabolites for full characterization.

Indexed as

SoftwareTandem Mass SpectrometryInternet

Identifiers

PMID41328747
PMCPMC12724678

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.