• search hit 10 of 14
Back to Result List

Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships

  • Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalableSpectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.show moreshow less

Download full text files

  • © 2021 Huber et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Florian HuberORCiD, Lars Ridder, Stefan Verhoeven, Jurriaan H. Spaaks, Faruk Diblen, Simon Rogers, Justin J. J. van der Hooft
open access (DINI-Set):open_access
Qualitätssicherung:peer reviewed
open access :Gold - Erstveröffentlichung mit Lizenzhinweis
Fachbereich/Einrichtung:Hochschule Düsseldorf / Fachbereich - Medien
Document Type:Article
Year of Completion:2021
Language of Publication:English
Publisher:Cold Spring Harbor Laboratory
Creating Corporation:PLOS
Parent Title (English):PLOS Computational Biology
Volume:17
Issue:2
Article Number:e1008724
URN:urn:nbn:de:hbz:due62-opus-34687
Related URL:http://www.ncbi.nlm.nih.gov/pubmed/33591968
DOI:https://doi.org/10.1371/journal.pcbi.1008724
ISSN:1553-7358
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
Release Date:2021/11/09
Note:
Data Availability Statement: The pre-processed, cleaned dataset with all positive ionization mode spectra can be downloaded from https://doi.org/10.5281/zenodo.3978118, the original raw data can be accessed from https://doi.org/10.5281/zenodo.3979010.

Funding: J.J.J.v.d.H. acknowledges funding from an ASDI eScience grant, ASDI.2017.030, from the Netherlands eScience Center—NLeSC, www.esciencecenter.nl, The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Accept ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.