InstaDeep

We’re excited to share that BenchMHC, our open-source Python framework to reproduce, retrain, and evaluate peptide-MHC presentation models, is now available on @github! 🚀
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Thank you all for a great @bitsinbio Paris!

On Tuesday this week, 70 of us gathered at our Paris office for three talks on proteins, cells and patients with @orakldotbio and @ScientaLab. 🇫🇷
Thanks to our speakers, and to everyone who joined us for the networking! 💪

Join @bitsinbio Paris, 22 Sept at the InstaDeep office! 🇫🇷

With State-space models for protein–protein interactions (InstaDeep), noise ceilings in cancer drug response prediction (@orakldotbio), and patient representations at scale (@ScientaLab).

🤝 Introducing STIX, InstaDeep's new JAX library for generative modelling, built on the stochastic interpolants framework.

STIX unifies flow matching, diffusion (including uniform and masked variants), and Bayesian flow networks under a single, common design space. 🧵

🎙️ Calling our shots. In episode 3 of the Let's Talk Research podcast, Senior Research Engineer Christoph Brunken and Staff Research Scientist Jules Tilly explored our future ambitions for machine-learned interatomic potentials (MLIPs).
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