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import streamlit as st |
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from rdkit.Chem import MACCSkeys |
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from rdkit import Chem |
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import numpy as np |
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import pandas as pd |
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import xgboost as xgb |
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from sklearn.metrics import f1_score, accuracy_score, average_precision_score, roc_auc_score |
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import rdkit |
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from rdkit.Chem.Scaffolds import MurckoScaffold |
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import pickle |
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device = 'cpu' |
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model_path = 'model/' |
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st.set_page_config( |
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page_title='Hello' |
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) |
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st.write('# JAK inhibiition prediction app') |
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st.sidebar.success('Select a page above') |
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st.markdown( |
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""" |
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* This is an open-source app framework built specifically for JAK inhibition of a certain drug with its SMILES as input. |
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* Suitable model(s) could be chosen for prediction based on your need (in JAK page). |
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* Simple machine learning models, tree models, graph-based models and bert models are trained ane evaluated (results in Model Evaluation page). |
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* Area uder the curve could also be drawn based on our test set results (in Plot AUC page). |
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Prediction should be used with caution and just for reference. |
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""") |
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