A set of Jupyter notebooks for learning Cheminformatics. The links below will open the tutorials on Google Colab.
This way you can run the notebooks without having to install software on your computer. Of course, you can also just
clone the repo and run these notebooks on your own computer.
- A Whirlwind Introduction to the RDKit for Cheminformatics
- A Brief Introduction to Pandas for Cheminformatics
- SMILES Tutorial
- SMARTS Tutorial
- Recursive SMARTS - Under Construction
- Reaction SMARTS - Under Construction
- Identifying Scaffolds
- R-group Analysis
- Positional Analogue Scanning
- Free-Wilson Analysis
- Matched Molecular Pairs - Under Construction
- Building a Classification Model
- Comparing Classification Models
- Building a Regression Model
- Comparing Regression Models
These notebooks began as part of a two-day workshop I did at the University of Bonn in 2019. Since then, the notebooks have evolved and additional notebooks have been added. A lot of the notebooks started as posts on my blog, Practical Cheminformatics. I originally had everything running on Binder, but I found some capacity limits with larger groups and moved everything to Google Colab. I'm planning to continue to add to and revise these as long as people are interested.
This is a work in progress. As you can see above, I'm still working on a few of the notebooks. It's more than possible that these tutorials contain mistakes and/or typos. If you find something that should be corrected, please submit an issue or a PR. In addition, I'm always looking to improve the text. Please let me know if there are aspects that could be explained more clearly. I'd also be interested in hearing about additional topics that you'd like to see covered.
These tutorials wouldn't be possible without the work of Greg Landrum, Brian Kelley and the RDKit team, as well as Cédric Bouysset and his work on mols2grid. Thanks!