Deep convolutional neural network for retention time prediction in Reversed-Phase Liquid Chromatography
Repository contains pre-trained models, data on retention times, one-hot matrices for five data sets (METLIN SMRT, MassBank1, MetaboBASE, Hilic_Retip and Riken_Retip). Scripts can be used to train 1D CNN model from scratch or for transfer learning approach. To reproduce results of predicition retention times for METLIN SMRT data set with 1D CNN check Report.
- To train 1D CNN on METLIN SMRT data set load zip file "Train initial model for SMRT"
- To train 1D CNN from scratch on MassBank1, MetaboBASE, Hilic_Retip and Riken_Retip data sets load zip files "List of matrices transfer data sets" and "SMILES and RTs"
- For transfer learning with MassBank1, MetaboBASE, Hilic_Retip and Riken_Retip data sets load zip files "List of matrices transfer data sets", "SMILES and RTs", "models for transfer learning"
- DATA also contains SDF files for MassBank1, MetaboBASE, Hilic_Retip and Riken_Retip data sets "SDF_DATA_SETS.zip". These files can be used to build your own model and to compare results with 1D CNN
The only requirements are to be familiar with the basic syntax of the R language, PC with Internet connection and Windows OS (desirable), RStudio and R (≥ 4.0.0).
Please send any comments or questions you may have to the author (Ms. Elizaveta Fedorova 👩🔬): ✉️ elizaveta.chemi@gmail.com, 