DEEPLEARNING

Deeplearning is a part of machine learnig and is part of artifitial inteligence.

!pip install DeepPurpose !pip install gradio !pip install rdkit-pypi !pip install git+https://github.com/bp-kelley/descriptastorus !pip install pandas-flavor import numpy as np import pandas as pd from DeepPurpose import utils from DeepPurpose import DTI as models import gradio model_binding = models.model_pretrained(model = 'MPNN_CNN_BindingDB') model_kiba = models.model_pretrained(model = 'MPNN_CNN_KIBA') model_davis = models.model_pretrained(model = 'MPNN_CNN_DAVIS') def DTI_pred(data, drug, target): if data == 'BindingDB': model = model_binding elif data == 'KIBA': model = model_kiba elif data == 'DAVIS': model = model_davis X_pred = utils.data_process(X_drug = [drug], X_target = [target], y = [0], drug_encoding = 'MPNN', target_encoding = 'CNN', split_method='no_split') y_pred = model.predict(X_pred) return str(y_pred[0]) gradio.Interface(DTI_pred, [gradio.inputs.Dropdown(label = "Training Dataset", choices = ['BindingDB', 'DAVIS', 'KIBA']), gradio.inputs.Textbox(lines = 5, label = "Drug SMILES"), gradio.inputs.Textbox(lines = 5, label = "Target Amino Acid Sequence")], gradio.outputs.Textbox(label = "Predicted Affinity")).launch(share=True)