ChemEmbed identifies metabolites by transforming an experimental MS/MS spectrum into a learned molecular embedding with a convolutional neural network, then ranking candidate structures from a reference database by cosine similarity against that predicted embedding.

Models and the reference database are not included and must be supplied separately.