Mass2SMILES is an open-source Python based deep learning approach for structure and functional group prediction from mass spectrometry data (MS/MS). Spectral data can be provided as MGF files (GNPS-syle) and model inference is most effciently performed via the provided docker container.
supplementary data with container and model at (you must have a vaild licence for NIST):
the pre-print is available at: https://doi.org/10.1101/2023.07.06.547963
# the container is available as tarball in supplementary or via docker pull delser292/mass2smiles:final
# unzip the docker.zip, the mass2smiles folder contains the model files and scripts to execute everything and it is important to specify the path to this folder when starting predictions.
# The predictions can be started through this command:
docker run -v c:/your_path/to_the_folder/mass2smiles/:/app mass2smiles:transformer_v1 conda run -n tf python app/mass2smiles_transformer.py your_mgf_file.mgf /appThe model architecture:
