- Generate graph feature database in a pickle file
- top_db.py : creates TOP feature database using RDKit
- qc1_3d.py : generates 3D molecular structures for the QC1 database
- qc1_db.py : aggregates the 3D structures and calculates features
- qc2_db.py : calculates BDE features for the QC2 model and stores them in a pickle file
- Run the prediction script with the associated model and database
- pred_afb.py : predict a spectra using the QC2 model
- Example:
cd weights/
cat qc2_1.model.a* > qc2_1.model
cd ../example
python ../qc2_db.py example.csv ex.pkl
python ../pred_qc2.py ./ex.pkl 30
cat pred_qc2.ms
- Collision Energy in eV
- InChI
- Smiles
- M/Z: numpy array of high resolution m/z values.
- Intensity: numpy array of MS intensities.
-
See data/msms_sample.pkl
-
Generate graph feature database in a pickle file
- top_db.py : creates TOP feature database using RDKit
- qc1_3d.py : generates 3D molecular structures for the QC1 database
- qc1_db.py : aggregates the 3D structures and calculates features
- qc2_db.py : calculates BDE features for the QC2 model and stores them in a pickle file
-
Test datasets are assigned by first training the control model with train_control.py
-
Test set data are located in test_set/
- torch
- torch-geometric
- alfabet https://github.com/NREL/alfabet
- xtb https://github.com/grimme-lab/xtb
- openbabel
- pandas
- matplotlib
- numpy
QC-GN2oMS2: a Graph Neural Net for High Resolution Mass Spectra Prediction
Richard Overstreet, Ethan King, Julia Nguyen, Danielle Ciesielski
bioRxiv 2023.01.16.524269; doi: https://doi.org/10.1101/2023.01.16.524269