Integrated omics analysis for small molecule-mediated host-microbiome interactions
Advancing our understanding of molecular mechanisms of health and disease
spec2vec is a novel similarity measure for comparing mass spectrometry data, which learns peak representations using Word2Vec.
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.
February 17, 2021