Metadata-Version: 2.1
Name: intrepppid
Version: 0.1.0
Summary: Protein-protein interaction prediction model that leverages orthology data
Home-page: https://github.com/Emad-COMBINE-lab/intrepppid
License: AGPL-3.0-or-later
Author: Joseph Szymborski
Author-email: joseph.szymborski@mail.mcgill.ca
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: fire (>=0.5.0,<0.6.0)
Requires-Dist: matplotlib (==3.6.3)
Requires-Dist: pandas (==2.2.0)
Requires-Dist: passlib (==1.7.4)
Requires-Dist: plyvel (==1.5.1)
Requires-Dist: pytorch-lightning (==1.9.1)
Requires-Dist: ranger21 (>=0.1.0,<0.2.0)
Requires-Dist: rich (==13.5.2)
Requires-Dist: scikit-learn (==1.2.1)
Requires-Dist: scipy (==1.12.0)
Requires-Dist: sentencepiece (==0.1.97)
Requires-Dist: tables (==3.9.2)
Requires-Dist: tensorboard (==2.15.1)
Requires-Dist: torch (==1.13.1)
Requires-Dist: torchmetrics (==0.11.1)
Requires-Dist: tqdm (==4.64.1)
Project-URL: Repository, https://github.com/Emad-COMBINE-lab/intrepppid
Description-Content-Type: text/markdown

# INTREPPPID

***IN**corporating **TR**iplet **E**rror for **P**redicting **P**rotein-**P**protein **I**nteractions using **D**eep Learning*

---


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).

## How to Use INTREPPPID

Here are some quick highlights, but be sure to [read the documentation](https://emad-combine-lab.github.io/intrepppid/) for more details!

### Installing

To install INTREPPPID, clone the repository and install the dependencies using `pip` and the `requirements.txt` file at
the root of the repository

```bash
git clone https://github.com/jszym/intrepppid
cd intreppid
python -m virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
```

### Training Models

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

```bash
python -m 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]((https://emad-combine-lab.github.io/intrepppid/)) for more details.

## License

INTREPPPID

***IN**corporating **TR**iplet **E**rror for **P**redicting **P**rotein-**P**protein **I**nteractions using **D**eep 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/>.
