DeepTrajectory is a deep recurrent neural network based on gated recurrent units to identify improved conformational states from refinement trajectory data in order to assist accurate protein structure prediction.
The pre-print is available on bioRxiv.
This repository contains the source code of the model together with helper functions to measure the performance during training and validation.
The data-set for training and testing can be downloaded from https://zenodo.org/record/1183354. This webpage contains links to the raw PDB files of all trajectories used in this work, the feature table in CSV format and the cross-validation assignment as a CSV file.
The following python dependencies are required to run the code: tensorflow (version 1.0.0), scikit-learn, numpy, pandas.
The ipython notebook in src/training_example.ipynb shows an example how to train the model. Please make sure that you have downloaded and extracted the CSV data to the sub folder data/.