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

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