General

save_hf_model_locally.py

• Huggingface models must be saved locally to run on the cluster
• argparse: TODO

fasta2spacedtable.py

• Convert a fasta to table of ID,S E Q U E N C E
• argparse

hf_util.py

• Common utilies
• More to go in here, commonalities between sequence/aa level classification

hf_similarity.py

• get similarity scores for fasta of proteins
• argparse
• logger: TODO

hf_aligner.py

• get amino acid similarities

Classify whole sequences

hf_classification.py

• Classify labeled sequences (ex. chloroplast localization)
• argparse
• logger
• evaluator: hf_evaluation.py

hf_evaluation.py

• Evaluate performance of sequence classification
• argparse
• logger: TODO

hf_predict.py

• Role potentially filled by hf_interpret.
• Apply classification model to new sequences: TODO
• argparse: TODO
• logger: TODO

hf_interpret.py

• Apply classification and get aa level explainations
• argparse
• logger: TODO

hf_embed.py

• Convert fasta to embedding
• argparse
• logger: TODO

hf_cluster.py

• Cluster sequence embeddings
• argparse: TODO
• logger:TODO

hf_interpret.py

• Get word importances for each sequence classification
• argparse: TODO
• logger:TODO

Classify amino acids

hf_classification_aa.py

• Classify individual amino acids
• argparse
• logger
• evaluator: TODO

hf_evaluate_aa.py : TODO

• Evaluate performance of sequence classification
• argparse: TODO
• logger: TODO

hf_predict_aa.py: TODO

• Apply classification model to new sequences: TODO
• argparse: TODO
• logger: TODO

Figure out what to do for interpretibility

Motifs from pretrained prot-bert

for each amino acid... Get embedding Get saliency map of each sequence https://colab.research.google.com/github/AndreasMadsen/python-textualheatmap/blob/master/notebooks/huggingface_bert_example.ipynb#scrollTo=X8GJbpoUmYdT

for each aa record saliency interactions, and embeddings of those interactions

compare similarity of embeddings.....