spec2vec

spec2vec is a novel similarity measure for comparing mass spectrometry data, which learns peak representations using Word2Vec.

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What spec2vec can do for you

  • Allows to learn abstract mass spectra representations from large mass spectral data sets (unsupervised learning).
  • Computes mass spectra similarities that show a high correlation with actual molecular similarity.

Spec2vec is a novel spectral similarity score inspired by a natural language processing algorithm -- Word2Vec. Where Word2Vec learns relationships between words in sentences, spec2vec does so for mass fragments and neutral losses in MS/MS spectra. The spectral similarity score is based on spectral embeddings learnt from the fragmental relationships within a large set of spectral data.

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Programming languages
  • Python 98%
  • Batchfile 1%
  • Makefile 1%
License
</>Source code

Participating organisations

Wageningen University & Research
Netherlands eScience Center
Hochschule Düsseldorf University of Applied Sciences
Life Sciences
Life Sciences
University of Glasgow

Reference papers

Mentions

Build a mass spectrometry analysis pipeline in Python using matchms — part II: Spec2Vec

Author(s): Florian Huber
Published in 2021

Build a mass spectrometry analysis pipeline in Python using matchms — part III: molecular…

Author(s): Florian Huber
Published in 2021

Contributors

Adam Belloum
Adam Belloum
Faruk Diblen
Faruk Diblen
Florian Huber
Florian Huber
Hanno Spreeuw
Hanno Spreeuw
Jurriaan H. Spaaks
Jurriaan H. Spaaks
JvdH
Justin J. J. van der Hooft
SR

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