We also introduce the DreaMS Atlas: a large-scale molecular network built from 200 million mass spectra, providing a new way to connect and analyze thousands of distinct scientific studies.

When fine-tuned, DreaMS achieves state-of-the-art performance across a range of molecule annotation tasks (e.g., predicting chemical similarity of molecular structures based on their mass spectra).

Trained in a self-supervised way on tens of millions of mass spectra from diverse samples (e.g., plants, human tissues, microbes, foods, soil samples), DreaMS learns rich representations ("embeddings") of molecular structures.

🚀 Exciting MassSpecGym leaderboard update 🚀

Two new machine learning models achieve up to a 300% improvement in de novo molecular generation given mass spectra and corresponding chemical formulae. 🔥 1/n

Check out our NeurIPS 2024 spotlight poster on MassSpecGym, a dataset and benchmark for discovering new molecules from nature 🌿. If you work on generative models for graphs/molecules, plug your model into MassSpecGym and see how many molecules you can discover! 🚀 1/6