Spec2Vec

Improved mass spectral similarity scoring through learning of structural relationships. 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. Analysis and benchmarking of mass spectra similarity measures using gnps data set.