PPR Motif Annotation using Neural Network

Overview

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.

Dependencies

To install python dependencies run: pip install -r requirements.txt

Todo

• 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.

Sequence logo of Arabidopsis thaliana PPR-like motif variants

P

P1

P2

L1

L2

S1

S2

SS

TPR

E1

E2