├── .gitignore ├── LICENSE ├── README.md ├── additional_encoding_tests.py ├── encoded_data └── rh02_rh03_prob_distribution.npy ├── notebooks ├── ANARCI_scores.pdf ├── AbLSTM_scores.pdf ├── BioPhi_scores.pdf ├── decoy_scores.csv ├── decoys.csv ├── decoys.fasta ├── decoys.txt ├── human-ness_scores.csv ├── orig.csv ├── orig.fasta ├── orig.txt ├── orig_scores.csv ├── sampled_harvest_decoy_seqs.fasta ├── sampled_harvested_autoencoder_labels.ptc ├── sampled_harvested_original_seqs.fasta └── score_autoencoder_seqs.ipynb ├── raw_data ├── placeholder.txt └── rh04_sequences.txt ├── requirements.txt ├── results_and_resources ├── 5x_CV_results.txt ├── ProtVec │ └── protVec_100d_3grams.csv ├── run_experiments.png ├── selected_sequences │ ├── Cluster marginal distributions.pdf │ ├── Clustering for final sequence set.png │ ├── Final_Selected_Sequences.txt │ ├── Mutation_scoring.csv │ ├── Score_distribution.pdf │ ├── Test_set_score_distribution.csv │ ├── cluster_marginal_distributions_source_data.csv │ ├── dendrogram.csv │ ├── score_variability.txt │ ├── top_1000_sequences.ptc │ ├── top_1000_sequences.txt │ ├── top_2000_sequences.ptc │ ├── top_2000_sequences.txt │ ├── top_4000_sequences.ptc │ ├── top_4000_sequences.txt │ ├── top_500_sequences.ptc │ └── top_500_sequences.txt ├── simulated_annealing │ ├── Scores for chain 0.pdf │ ├── Scores for chain 1.pdf │ ├── Scores for chain 2.pdf │ ├── Scores for chain 3.pdf │ ├── Scores for chain 4.pdf │ ├── Scores for chain 5.pdf │ ├── Scores for chain 6.pdf │ ├── Scores for chain 7.pdf │ ├── Scores for chain 8.pdf │ ├── Scores for chain 9.pdf │ ├── annealing_seqs_all_pos.txt │ └── markov_chain_scores.csv ├── task_adapted_ae_linlayer_subsampled.py ├── test_set_results.txt ├── trained_models │ ├── Subsample0.01_TaskAdapted_Autoencoder.ptc │ ├── Subsample0.1_TaskAdapted_Autoencoder.ptc │ ├── Subsample0.5_TaskAdapted_Autoencoder.ptc │ ├── TaskAdapted_Autoencoder.ptc │ ├── Unadapted_Autoencoder.ptc │ ├── ablang_trainset_only_BON_model.ptc │ ├── ablang_trainset_only_FCNN_model.ptc │ ├── adapted_trainset_only_BON_model.ptc │ ├── adapted_trainset_only_FCNN_model.ptc │ ├── antiberty_full_trainset_only_BATCHED_BON_model.ptc │ ├── antiberty_full_trainset_only_BATCHED_FCNN_model.ptc │ ├── antiberty_trainset_only_BON_model.ptc │ ├── antiberty_trainset_only_FCNN_model.ptc │ ├── atezolizumab_varbayes_model.ptc │ ├── fair_esm_trainset_only_BON_model.ptc │ ├── fair_esm_trainset_only_FCNN_model.ptc │ ├── nonadapted_trainset_only_BON_model.ptc │ ├── onehot_trainset_only_BON_model.ptc │ ├── onehot_trainset_only_FCNN_model.ptc │ ├── protvec_trainset_only_BON_model.ptc │ ├── protvec_trainset_only_FCNN_model.ptc │ ├── s10_trainset_only_BON_model.ptc │ ├── s10_trainset_only_FCNN_model.ptc │ ├── s1_trainset_only_BON_model.ptc │ ├── s1_trainset_only_FCNN_model.ptc │ ├── s25_trainset_only_BON_model.ptc │ ├── s25_trainset_only_FCNN_model.ptc │ ├── s50_trainset_only_BON_model.ptc │ ├── s50_trainset_only_FCNN_model.ptc │ ├── task_adapted_ae_linlayer_subsampled.py │ ├── unirep_trainset_only_BON_model.ptc │ └── unirep_trainset_only_FCNN_model.ptc ├── trastuzumab.txt └── wt_anarci_numbering.txt ├── run_experiments.py ├── src ├── autoencoder_training_scripts │ └── train_models.py ├── model_code │ ├── __init__.py │ ├── batched_trad_nn_classification.py │ ├── task_adapted_ae_linlayer_subsampled.py │ ├── task_adapted_autoencoder.py │ ├── traditional_nn_classification.py │ ├── unadapted_autoencoder.py │ ├── variational_Bayes_ordinal_BATCHED.py │ └── variational_Bayes_ordinal_reg.py ├── model_training │ ├── autoencoder_training.py │ ├── cv_scoring.py │ └── model_training_code.py ├── raw_data_processing │ └── process_raw_reads.py ├── sequence_encoding │ ├── Unirep_encoding.py │ ├── alternate_encoding.py │ ├── antibody_lang_mods.py │ ├── encode_fair_esm.py │ ├── encode_sequences.py │ ├── fair_esm_wrapper.py │ └── seqs_to_fasta.py ├── simulated_annealing │ ├── __init__.py │ ├── markov_chain_direv.py │ └── run_markov_chains.py ├── trastuzumab_exp │ ├── __init__.py │ └── process_raw_seqs.py └── utilities │ └── model_data_loader.py └── trastuzumab_data ├── raw_data ├── anarci_check2.csv_H.csv ├── mHER_H3_AgNeg.csv ├── mHER_H3_AgPos.csv └── trastuzumab_anarci.txt_H.csv ├── results_and_resources ├── Uncertainty_vs_pred.png ├── model_exp_scores.csv ├── model_exp_scores.png ├── model_training_scores.csv ├── model_training_scores.png ├── trained_models │ └── adapted_trainset_only_BON_model.ptc └── uncertainty_vs_pred.csv └── selected_55.txt /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wang-lab-UCSD/RESP/HEAD/.gitignore -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wang-lab-UCSD/RESP/HEAD/LICENSE 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