Identifying molecules and predicting the identity of unknown substances play huge roles in discovering natural products that can be used in drugs to treat cancers, viral infections and other ailments. Researchers in the Computational Biology Department have recently made important strides to improve and accelerate these processes. In one study, a team developed algorithms that match the signals of a microbe's metabolites with its genomic signals and identify which ones likely correspond to a natural product that could be used in drug development. In another, the team created an algorithm that uses mass spectrometry data from molecules to predict an unknown substance's identity, telling scientists early in their research if they've stumbled on something new.