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{"Alzheimer": {"description": "Case for Alzheimer with trained FEDOT pipelines for predict \"docking_score\", and \"IC50\"", "generative_models": {"data_path": "infrastructure/generative_models/docked_data_for_train/data_4j1r.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/many_prop_CVAE/weights_8p_alzhmr", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/Alzheimer/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_Alzheimer_regression", "classification": "infrastructure/automl/train_model_data/trained_data_Alzheimer_classification"}, "metric": {"regression": {"rmse": 1.029}, "classification": {"roc_auc_pen": 0.993}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "___TEST___": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/___TEST___/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data____TEST____regression", "classification": null}, "metric": {"regression": {"MAE score": 0.45800730387755123, "MSE score": 0.6897766297937279, "R2 score": 0.54351781995021}, "classification": null}, "Predictable properties": {"regression": ["docking_score", "IC50"]}}}, "BTK": {"description": "Case for Sclerosis with trained FEDOT pipelines for predict \"IC50\"", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/BTK/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/train_BTK/BTK/weights", "arch_type": null, "metric": 0.0828026499603948}, "ml_models": {"data_path": "infrastructure/automl/data/BTK/data.csv", "feature_column": ["smiles"], "target_column": ["target"], "status": "Trained", "weights_path": {"regression": null, "classification": "infrastructure/automl/train_model_data/trained_data_BTK_classification"}, "metric": {"regression": null, "classification": {"Accuracy score": 0.8857, "F1 score": 0.9123}}, "Predictable properties": {"classification": ["target"]}}}, "PIC50_predictor": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/PIC50_predictor/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["pIC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_PIC50_predictor_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["pIC50"]}}}, "pIC50_predictor": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/pIC50_predictor/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["pIC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_pIC50_predictor_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.41648080383401553, "MSE score": 0.34705665974860733, "R2 score": 0.729817357841055}, "classification": null}, "Predictable properties": {"regression": ["pIC50"]}}}, "PAINS_predictor": {"description": "", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/PAINS_predictor/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/train_PAINS_predictor/PAINS_predictor/weights", "arch_type": null, "metric": 0.010749513783406384}, "ml_models": {"data_path": "infrastructure/automl/data/PAINS_predictor/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["PAINS"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_PAINS_predictor_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.7177099249650927, "MSE score": 1.2618142805349875, "R2 score": 0.5238247840674277}, "classification": null}, "Predictable properties": {"regression": ["docking_score"]}}}, "pIC50_prediction": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/pIC50_prediction/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["pIC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_pIC50_prediction_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["pIC50"]}}}, "IC50_prediction": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_prediction/data.csv", "feature_column": ["Smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_prediction_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.10213080739155726, "MSE score": 0.03921116436250394, "R2 score": 0.68699877623761}, "classification": null}, "Predictable properties": {"regression": ["IC50"]}}}, "Docking_score_pred": {"description": "", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/Docking_score_pred/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/train_Docking_score_pred/Docking_score_pred/weights", "arch_type": null, "metric": 0.3092724550256598}, "ml_models": {"data_path": "infrastructure/automl/data/Docking_score_pred/data.csv", "feature_column": ["Smiles"], "target_column": ["docking_score"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_Docking_score_pred_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.6854647891110414, "MSE score": 1.068066480611931, "R2 score": 0.5818186574632519}, "classification": null}, "Predictable properties": {"regression": ["docking_score"]}}}, "Test_ivan": {"description": "Case for Sclerosis with trained FEDOT pipelines for predict \"IC50\"", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/Test_ivan/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_Test_ivan", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/Test_ivan/data.csv", "feature_column": ["smiles"], "target_column": ["target"], "status": "Trained", "weights_path": {"regression": null, "classification": "infrastructure/automl/train_model_data/trained_data_Test_ivan_classification"}, "metric": {"regression": null, "classification": {"Accuracy score": 0.8857142857142857, "F1 score": 0.8518518518518519}}, "Predictable properties": {"classification": ["target"]}}}, "Base": {"description": "Case for Sclerosis with trained FEDOT pipelines for predict \"IC50\"", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/Base/data.csv", "feature_column": ["smiles"], "target_column": [], "status": "Trained", "weights_path": {"regression": null, "classification": null}, "metric": {"regression": null, "classification": null}, "Predictable properties": {}}}, "test_case_async": {"description": "Descrption not provided", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/test_case_async/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/train_test_case_async/test_case_async/weights", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_case_async/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_test_case_async_regression", "classification": null}, "metric": {"regression": {"MAE score": 1833.4771447327198, "MSE score": 26122143.40066156, "R2 score": -0.7483822150035182}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "test_case_async_daemon": {"description": "test run of daemon", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/test_case_async_daemon/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_test_case_async_daemon", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_case_async_daemon/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_test_case_async_daemon_regression", "classification": null}, "metric": {"regression": {"MAE score": 15249.171706795103, "MSE score": 8604780212.231148, "R2 score": -0.014440756273400801}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "test_case_async_daemon_v2": {"description": "test run of daemon", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/test_case_async_daemon_v2/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_test_case_async_daemon_v2", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_case_async_daemon_v2/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_test_case_async_daemon_v2_regression", "classification": null}, "metric": {"regression": {"MAE score": 15315.37639558455, "MSE score": 8592207987.34364, "R2 score": -0.01295858275956796}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "test_case_async_daemon_v3": {"description": "test run of daemon", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_case_async_daemon_v3/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_test_case_async_daemon_v3_regression", "classification": null}, "metric": {"regression": {"MAE score": 15483.478400078, "MSE score": 8587289344.55542, "R2 score": -0.01237871068999108}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "test_case_async_daemon_v4": {"description": "test run of daemon", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_case_async_daemon_v4/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_test_case_async_daemon_v4_regression", "classification": null}, "metric": {"regression": {"MAE score": 15979.18185628933, "MSE score": 8565172588.142844, "R2 score": -0.009771306602017082}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "BTK_affinity_prediction": {"description": "Predictive model for Brutone's tyrosine kinase affinity using SMILES features", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/BTK_affinity_prediction/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_BTK_affinity_prediction", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/BTK_affinity_prediction/data.csv", "feature_column": ["smiles"], "target_column": ["affinity_value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_BTK_affinity_prediction_regression", "classification": null}, "metric": {"regression": {"MAE score": 15008.182147137859, "MSE score": 8632589938.309528, "R2 score": -0.01771931991580611}, "classification": null}, "Predictable properties": {"regression": ["affinity_value"]}}}, "GSK_IC50_demo": {"description": "Training predictive model for GSK_IC50_demo using GSK_IC50_chembl_preprocessed.csv dataset with log_affinity as target", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/GSK_IC50_demo/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_GSK_IC50_demo", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/GSK_IC50_demo/data.csv", "feature_column": ["smiles"], "target_column": ["log_affinity"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_GSK_IC50_demo_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.535688363522795, "MSE score": 0.44131530730459906, "R2 score": 0.6453176397959515}, "classification": null}, "Predictable properties": {"regression": ["log_affinity"]}}}, "MEK_Ki_demo": {"description": "Training predictive model for MEK_Ki_demo using MEK1_Ki_chembl_preprocessed.csv dataset", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/MEK_Ki_demo/data.csv", "feature_column": ["smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_MEK_Ki_demo", "arch_type": null, "metric": null}, "ml_models": {"data_path": 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"metric": {"regression": null, "classification": null}, "Predictable properties": {}}}}