5 papers
Sustainable Materials Discovery in the Era of Artificial Intelligence
Sajid Mannan, Rupert J. Myers, Rohit Batra +3
Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening. Yet current genera…
TACK: A Statistical Evaluation of Degradation Activity on a Novel TArgeting Chimeras Knowledge Dataset
Stefano Ribes, Nils Dunlop, RocÃo Mercado
Proteolysis-targeting chimeras (PROTACs) represent a promising therapeutic modality that induces targeted protein degradation by hijacking the ubiquitin-proteasome system. However,…
deCIFer: Crystal Structure Prediction from Powder Diffraction Data using Autoregressive Language Models
Frederik Lizak Johansen, Ulrik Friis-Jensen, Erik Bjørnager Dam +3
Novel materials drive advancements in fields ranging from energy storage to electronics, with crystal structure characterization forming a crucial yet challenging step in materials…
LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models
Siddharth Betala, Samuel P. Gleason, Ali Ramlaoui +12
Generative machine learning (ML) models hold great promise for accelerating materials discovery through the inverse design of inorganic crystals, enabling an unprecedented explorat…
Compressing Biology: Evaluating the Stable Diffusion VAE for Phenotypic Drug Discovery
Télio Cropsal, RocÃo Mercado
High-throughput phenotypic screens generate vast microscopy image datasets that push the limits of generative models due to their large dimensionality. Despite the growing populari…