Till Siebenmorgen

[Nature Computational Science @NatComputSci]

📢 New today! @PopowiczLab, @t7morgen7, @FilipeMMenezes and colleagues introduce MISATO, a database for structure-based drug discovery. @helmholtz_ai, @Sattler_lab, @HelmholtzMunich https://t.co/wLp8wrtb0X

[Till Siebenmorgen @t7morgen7]

Very excited that MISATO is now published in Nature Computational Science. Check out the dataset to train the next generation of ML models for structure based drug discovery. All data and baseline models are freely available.
https://t.co/34BeAIIfpw

[Helmholtz Munich | @HelmholtzMunich @HelmholtzMunich]

A team of researchers unveil the MISATO dataset for training #AI models in #drugdiscovery.
Its realistic molecular representations promise a leap forward in medicine & pharmaceuticals.
👉Read more: https://t.co/ybpVeLdNi1

[Filipe Menezes @FilipeMMenezes]

Next Thursday (22.06) me and @t7morgen7 will give a talk on the MISATO DB. Don't miss!
Where: https://t.co/kudha2Mn9w
When: 11:30 a.m. CET

Thank Computational Biochemistry Group from Univ. Porto

[Tess van Stekelenburg @velvetatom]

10/

🧪MISATO + molecular dynamics!

Til Siebermorgen (@t7morgen7) & team trained GNN's & LLM's ontop of the MISATO dataset & built a space that lets you drop in any PDB of interest to predict molecular dynamics / protein adaptability.

https://t.co/FrWb3HxEkK

[Popowicz Lab @PopowiczLab]

Artificial Intelligence is in urgent need of more refined datasets for drug discovery applications! Here is our contribution, the MISATO dataset: https://t.co/Q2cKkiMjQC

[Filipe Menezes @FilipeMMenezes]

The pre-print of our Energy Decomposition Analysis is finally out =)
https://t.co/ilJI4EymsH

[Till Siebenmorgen @t7morgen7]

Super excited to present MISATO a machine learning dataset of protein-ligand complexes for structure based drug discovery.

preprint: https://t.co/yfxnV6LIzn
github: https://t.co/e0lDfftLAj

[Filipe Menezes @FilipeMMenezes]

Our pre-print for the MISATO database, for ML applications is now out! https://t.co/PXrTnw56JB