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caswognum.nl
Trying to teach machines (and myself) drug discovery at Valence Labs and Polaris. www.caswognum.nl 🇳🇱🇨🇦
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In case you missed it!

Join us tomorrow to hear @peterskrinjar.bsky.social talk about 🌹 Runs N' Poses 🌹! Curious to hear your thoughts on how to keep up with benchmarking in this field.

⚡ The intermediate leaderboard for the antiviral challenge is now live! 👀 See how you placed: antiviral.polarishub.io The challenge officially ends on March 10th, but there's one last leaderboard update before the final results. Submit before midnight on Feb 26th! polarishub.io/competitions

We’re hosting @peterskrinjar.bsky.social for a webinar to discuss his latest paper “Have protein co-folding methods moved beyond memorization?”! Join live on Feb 21st at 11 AM ET. Register here: us06web.zoom.us/webinar/regi... Explore Runs N’ Poses on Polaris today: polarishub.io/benchmarks/p...

Endless views and impressive cloudscapes! #photography #lions #kenya #maasaimara #simba

We’re extremely excited to host Runs N’ Poses on Polaris! The authors show how current co-folding methods struggle to generalize beyond ligand poses in their training data. Explore the benchmark: polarishub.io/benchmarks/p... Explore the dataset: polarishub.io/datasets/pli...

New leaderboard on @polarishub.io for Runs 'N Poses! 🎸 Anyone has any protein-ligand co-folding methods laying around they would like to put to the test? polarishub.io/benchmarks/p... Great work @peterskrinjar.bsky.social @jeeberhardt.bsky.social @torstenschwede.bsky.social @ninjani.bsky.social

Excited to share our latest preprint evaluating AlphaFold3, Boltz-1, Chai-1 and Protenix for predicting protein-ligand interactions, featuring our newly introduced benchmark dataset 🌹Runs N’ Poses🌹! www.biorxiv.org/content/10.1... 🧵👇 (1/n)

Big milestone for @polarishub.io. We merged our first external contribution, thanks to @fastprop.bsky.social! 🎉 github.com/polaris-hub/... #opensource #benchmarking #ml #drugdiscovery

🚨 Extension Alert: The intermediate leaderboard submission deadline for the antiviral challenge has been extended to midnight on February 7th! Don't miss this chance to see how you stack up against other participants! Submit your results today: polarishub.io/competitions

With @polarishub.io we early on decided to purposefully restrict the flexibility of our datasets and benchmarks. We understand that this can be frustrating at times, but we believe it’s an important step to improve reproducibility. Our team is here to help if you need support! Reach out on Github.

💡Have questions about the data behind the antiviral challenge?💡 This week, @asapdiscovery.bsky.social and @omsf.io are hosting 3 virtual office hour sessions with the experimentalists behind the data! RSVP here: docs.google.com/forms/d/e/1F...

Only a few days left to submit your predictions for the first, intermediate leaderboard. We’ve got an incredibly passionate team on standby to help solve any issues you may run into and we’d love to hear your feedback. 🧑‍💻 Github: github.com/polaris-hub/... 💬 Discord: discord.gg/vBFd8p6H7u

If you have been waiting for the right time to start working on the ASAP Discovery challenge, this is it! 🏆 For all results submitted up until January 31st, we will publish an intermediate leaderboard. Get your first set of results in now and see how you stack up against your peers.

The @polarishub.io discord is feeling very lively right now. I love learning with and from all of you!💡 If you haven't yet, join us and put your methods to the test to learn what is working and what's not in ADMET, potency and pose prediction. Get started in a few lines of code. Great video by Lu!

Incredibly excited to see how well ADMET, affinity, and pose prediction models *actually* perform in the ASAP x OpenADMET x PolarisHub blind challenge: polarishub.io/competitions

Working on predictive models for drug discovery? Here's your chance to see how well your models actually work! Together with @polarishub.io and OpenADMET, we've launched a blind prospective challenge to see how well predictive models for drug discovery can actually predict real drug discovery data!

The @asapdiscovery.bsky.social x OpenADMET (@omsf.io) blind challenge is live! 🚀 You're free to use any publicly available training data, but the challenge provides 770 ligand poses, 1031 potency datapoints and 434 ADMET datapoints as a consistently generated training set. Come learn with us! 🏆

🎥 At NeurIPS, we had the opportunity to chat with the authors of several dataset and benchmarking papers that are relevant to machine learning for drug discovery. First up—a quick interview with the team behind WelQrate! 🧵 youtu.be/pbatKLphJAE

🎉 Zarr-Python 3 is here! 🎉 - Full support for Zarr v3 spec - Chunk-sharding for more efficient data storage - Major performance boosts with async I/O & parallel compression 💻 pip install --upgrade zarr 💻 conda install --channel conda-forge zarr Blog post: https://buff.ly/3C3OwYw

Hi, Zarr community! 👋 🚨 Big news: Zarr-Python 3.0 is dropping next week! 🚨 If your project depends on Zarr-Python, make sure to check out the migration guide to get ready for the update. Guide: https://buff.ly/3W0cLxd More updates soon! 🧑🏻‍💻

Vaderland! 🇳🇱 #netherlands #photography

Scar! 🦁 #lion #photography #kenya #maasai #mara

To change benchmarking practices in ML for drug discovery, I've always felt strongly we need to go beyond publishing papers. Excited to share a first glimpse into what that could look like! 👀

This is exactly our strategy with @polarishub.io! We want to provide ML-ready datasets that make it easy to do the right thing and hard to do the wrong thing.

We’re at #NeurIPS2024! Catch @jonnyhsu.bsky.social at the BELKA Competition workshop with the @leashbio.bsky.social team, where he’ll give an overview of Polaris. Tune in at 3:00 PM in the West meeting rooms 215 and 216. Find the full schedule: neurips.cc/virtual/2024...

@polarishub.io no longer just hosts small-molecule datasets! The release of RxRx3-Core is a testament to the work the team has done this last quarter to drastically improve the scalability of our platform. We're ready for a challenge! What XXL dataset (I'm talking TiBs!) should we host in 2025?