INTREPPPID

INcorporating TRiplet Error for Predicting Protein-Protein Interactions using Deep Learning

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INTREPPPID is a deep learning model for predicting protein interactions. It's especially good at making prediction on species other than those it was trained on (cross-species prediction).

You can find more information from our pre-print.

How to Use INTREPPPID

Here are some quick highlights, but be sure to read the documentation for more details!

Installing

The easiest way to install PPI Origami is to use pip to retrieve the PPI Origami release from PyPI.

pip install intrepppid

Alternatively, clone the repository and use poetry to install the dependencies

git clone https://github.com/jszym/intrepppid
cd intreppid
poetry install

Training Models

To train INTREPPPID, simply use the train e2e_rnn_triplet command like so:

intrepppid train e2e_rnn_triplet DATASET.h5 spm.model 3 100 80 --seed 3927704 --vocab_size 250 --trunc_len 1500 --embedding_size 64 --rnn_num_layers 2 --rnn_dropout_rate 0.3 --variational_dropout false --bi_reduce last --workers 4 --embedding_droprate 0.3 --do_rate 0.3 --log_path logs/e2e_rnn_triplet --beta_classifier 2 --use_projection false --optimizer_type ranger21_xx --lr 1e-2

Documentation

Be sure to read the documentation for more details.

Citation

If you use or refer to INTREPPPID, kindly cite our pre-print:

Joseph Szymborski, Amin Emad. INTREPPPID - An Orthologue-Informed Quintuplet Network for Cross-Species Prediction of Protein-Protein Interaction. bioRxiv. 2024 Jan 1; DOI:2024.02.13.580150.

also available in BibTex format:

@article{Joseph Szymborski_Amin Emad_2024,
  title={INTREPPPID - An Orthologue-Informed Quintuplet Network for Cross-Species Prediction of Protein-Protein Interaction},
  DOI={10.1101/2024.02.13.580150},
  journal={bioRxiv},
  author={Joseph Szymborski and Amin Emad},
  year={2024},
  month=jan,
  pages={2024.02.13.580150}
}

License

INTREPPPID

INcorporating TRiplet Error for Predicting Protein-Protein Interactions using Deep Learning

Copyright (C) 2023 Joseph Szymborski

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.