🌟Blog status🌟
Welcome to my blog on selected cheminformatics, machine learning and data science projects in drug discovery.
- Latest project - Please see updated web links for logistic regression under machine learning below
- Next project in the pipeline - Started on compiling own data and perhaps a deep learning one about ADRs
🌟Past projects🌟
Machine learning
Tree series - Decision tree 1 - data collection and preprocessing, 2 - data preprocessing and transformation, 3 - model building and estimating experimental errors, Random forest - model building, imbalanced dataset, feature importances & hyperparameter tuning, Random forest classifier - more on imbalanced dataset, Boosted trees - AdaBoost, XGBoost and Scikit-mol
Logistic regression 1 - Parquet file in Polars dataframe library, 2 - Preprocessing data in Polars dataframe library, 3 - Building logistic regression model using scikit-learn, 4 - Evaluating logistic regression model in scikit-learn, older long version
Data explorations
Cytochrome P450 and small drug molecules with a focus on CYP3A4 and CYP2D6 inhibitors
Working with scaffolds in small molecules - Manipulating SMILES strings
Molecular similarities in selected COVID-19 antivirals - Using RDKit’s similarity map and fingerprint generator
Web applications
Molecular visualisation web application - Interactive data table, Using Shiny for Python web application framework
Shinylive app in Python - Data preparation, Embedding app in Quarto document & using pyodide.http