3 papers
cs.LG2026
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
Kieran Didi, Zuobai Zhang, Guoqing Zhou +11
Protein interaction modeling is central to protein design, which has been transformed by machine learning with applications in drug discovery and beyond. In this landscape, structu…
cs.LG2026
One protein is all you need
Anton Bushuiev, Roman Bushuiev, Olga Pimenova +9
Generalization beyond training data remains a central challenge in machine learning for biology. A common way to enhance generalization is self-supervised pre-training on large dat…
cs.LG2025
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
Peter St. John, Dejun Lin, Polina Binder +89
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increas…