Nouvelles et reportages

Exploring the structural changes driving protein function with BioEmu-1
| Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Victor García Satorras, Osama Abdin, Bas Veeling, Ryota Tomioka, et Frank Noé
Meet BioEmu-1 from Microsoft Research. This deep learning model can generate thousands of protein structures per hour, unlocking new possibilities for protein scientists and drug discovery and research.

MatterGen: A new paradigm of materials design with generative AI
| Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Ryota Tomioka, et Tian Xie
Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments.

MatterGen: Property-guided materials design
| Andrew Fowler, Matthew Horton, Ryota Tomioka, Robert Pinsler, Tian Xie, Claudio Zeni, et Daniel Zügner
The central problem in materials science is to discover materials with desired properties. MatterGen enables broad property-guided materials design.