PPR Motif Annotation is a neural network based method for accurately predicting different variants of PPR motif, which is essential to extract PPR code thus large-scale predictions of PPR targets.
This repository contains code and pre-trained Keras model to run and deploy the Flask app together with code and data used to train the model and evaluating the model's performance.
To install python dependencies run: pip install -r requirements.txt
- Bugs
- Handling inputs.
- Bed format coordinates (0-based exclusive) of the features.
- Ending positions of the features.
- Optimization
- Variable length features (pad_sequences?).
- Unbalanced training set (sample_weight?).
- Under-represented classes (class_weight?).
- Enhancement
- Setting maximum number of query sequences.
- Loading example query sequences from file.
- Uploading query sequences from file.
- Displaying and downloading annotations in either bed or GFF3 format.
P
P1
P2
L1
L2
S1
S2
SS
TPR
E1
E2
