M6 Mac Mini as the prize for the Marimo Cheminformatics notebook competition!
marimo@marimo.io · 2w agoFor our cheminformatics competition, you can now win an @Apple Mac Mini M6. You have 1 month left to take a dataset and build a marimo notebook that brings cheminformatics to life. Competition details below.
A great opportunity to showcase your marimo skills and compete for some solid prizes. Looking forward to seeing what the community builds.
marimo@marimo.io · 2w ago33 days to win a mac mini. the challenge: pick a cheminformatics dataset and build a marimo notebook that answers a question you want the answer to. we're judging based on creativity, not on model accuracy. co-hosted with @wpwalters.bsky.social. we'll see you in our submissions 👀
Excited to team up with @marimo to explore new relationships between chemical structures and biological data. Bring your creativity, push the boundaries of reactive notebooks, and compete for prizes! Details below 👇
marimo@marimo.io · 4w agoWe're running a cheminformatics notebook competition with @wpwalters.bsky.social and OpenADMET. Take a dataset & bring cheminformatics to life. Mac Mini + $2.5K in prizes, deadline Oct 4 👀
New Practical Cheminformatics Post, "Useful RDKit Utils - A Mötley Collection of Helpful Routines" patwalters.github.io/Useful-RDKit...
The latest Practical Cheminformatics post, “The Trouble With Tautomers,” emerged from a discussion about the impact of tautomers on machine learning model predictions. patwalters.github.io/The-Trouble-...
The Trouble With Tautomers
IntroductionOne factor often overlooked when applying machine learning (ML) in small-molecule drug discovery is the influence of tautomers on model predictions. Drug-like molecules, especially those c...
patwalters.github.io
The latest addition (#33) to the Practical Cheminformatics Tutorials series explores Bayesian optimization of reaction conditions. github.com/PatWalters/p...
In a new Practical Cheminformatics post titled "Even More Thoughts on ML Method Comparisons," I share several plots that I find valuable for comparing machine learning methods. practicalcheminformatics.blogspot.com/2025/03/even...
Even More Thoughts on ML Method Comparisons
Introduction A few things motivated this post. Some recent discussions about the virtues of LightGBM vs XGBoost Posts on TabPFN by Jon...
practicalcheminformatics.blogspot.com
Determine bond order from XYZ format of molecule #RDKit As readers know that recent version of RDKit supports XYZ format which is used in quantum chemistry field. The format doesn't have information of bond order. So to re-construct from the information bond order determination step is required.…
Determine bond order from XYZ format of molecule #RDKit
As readers know that recent version of RDKit supports XYZ format which is used in quantum chemistry field. The format doesn't have information of bond order. So to re-construct from the information bond order determination step is required. Recently I found useful function for determining the order in rdkit and Greg wrote useful post almost two years ago I think it's worth to read.
iwatobipen.wordpress.com
Machine Learning in Drug Discovery Resources page updated for 2025. github.com/PatWalters/r...
GitHub - PatWalters/resources_2025: Machine Learning in Drug Discovery Resources 2024
Machine Learning in Drug Discovery Resources 2024. Contribute to PatWalters/resources_2025 development by creating an account on GitHub.
github.com
Deep learning for proteins tutorial: github.com/Graylab/DL4P...
GitHub - Graylab/DL4Proteins-notebooks: Colab Notebooks covering deep learning tools for biomolecular structure prediction and design
Colab Notebooks covering deep learning tools for biomolecular structure prediction and design - Graylab/DL4Proteins-notebooks
github.com
Excellent new paper (with code) by my former colleagues Steven Kearnes and Patrick Riley describing a procedure for associating confidence levels with regression model predictions in drug discovery. pubs.acs.org/doi/10.1021/...
Ordinal Confidence Level Assignments for Regression Model Predictions
We present a simple method for assigning accurate confidence levels to molecular property predictions from regression models. These confidence levels are easy to interpret and useful for making decisi...
pubs.acs.org
Many of you have seen Gabriele Corso's response to our recent preprint. If you haven't, it's here. www.linkedin.com/pulse/respon...
Response to Jain et al.
You may have seen a recent pre-print [1] from Jain et al. with strongly worded claims against the experimental results in our DiffDock paper [2].
linkedin.com
I'm thrilled to announce a new preprint describing collaborative work with Ajay Jain and Ann Cleves Jain, "Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows". arxiv.org/abs/2412.02889
Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows
The diffusion learning method, DiffDock, for docking small-molecule ligands into protein binding sites was recently introduced. Results included comparisons to more conventional docking approaches, wi...
arxiv.org
There’s a new Practical Cheminformatics post, “Some Thoughts on Dataset Splitting,” (with code and a robot cartoon) at practicalcheminformatics.blogspot.com/2024/11/some... .
