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TMBB LSTM

Bidirectional LSTM (PyTorch) for TMBB protein sequence generation.


Install

pip install torch numpy

Data

<basename>_train.fasta
<basename>_valid.fasta

Train

Here is an example of using the script for a dataset with basename "iiab_tmbb".

python3 lstm_lm_bidirectional.py <basename> <outfolder> 10 1 1024 rmsprop 1e-4 250 \
  --lstm_num_nodes 128 \
  --lstm_frag_size 50 \
  --gpu_device 0 \
  --task training

Inference

Here is the format for using this script for inferene (after the training run).

python3 lstm_lm_bidirectional.py <basename> <outfolder> ... \
  --task inference \
  --lstm_num_nodes <n> \
  --lstm_frag_size <n> \
  --method <greedy|pure|topk|nucleus>

Output

For the training run, the script produces the folowing output files:

  • model_<epoch>
  • train_evolution.tsv
  • epoch_<epoch>.fasta

For the inference run, the script produces the following output file:

  • valid_evolution.tsv

About

Long Short-Term Memory (LSTM) network for Transmembrane beta barrel (TMBB) generation

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