My brief background introduction can be accessed here via my blog, which showcases several different cheminformatics, machine learning and data science projects using various software toolkits. The latest project I've worked on is about cytochrome P450 and approved drugs.
There are also several other projects I've worked on over the past year or so such as:
- Tree series in machine learning on ChEMBL-derived data (decision tree 1, decision tree 2, decision tree 3, random forest, random forest classifier, boosted trees).
- Working with scaffolds in small molecules - Manipulating SMILES strings
- Molecular visualisation (Molviz) web application - Using Shiny for Python web application framework (interactive data table part)
- Shinylive app in Python - Embedding app in Quarto document (app embedded in web page) & using pyodide.http to import csv files
- Small molecules in ChEMBL database - series 1.1 - Polars dataframe library and machine learning in scikit-learn, series 1.2 - cross-validation & hyper-parameter tuning with scikit-learn and series 1.3 - re-training & re-evaluation with scikit-learn
Open-source contributions: practical_cheminformatics_tutorials, chembl_downloader