Protein-protein interaction prediction model that leverages orthology data
Project description
INTREPPPID
INcorporating TRiplet Error for Predicting Protein-Pprotein Interactions using Deep 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 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
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:
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 for more details.
License
INTREPPPID
INcorporating TRiplet Error for Predicting Protein-Pprotein 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/.
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