Ivan Barvik

A new RNA foundation model, published in Nature. Researchers introduce structRFM, an open, structure-guided RNA foundation model trained on 21 million RNA sequence–structure pairs. Unlike conventional RNA language models that primarily learn from sequences, structRFM incorporates base-pairing information directly into pre-training, enabling joint learning of RNA sequence and structure. Key highlights: • Structure-guided pre-training: A new masked language modeling strategy (SGMLM) captures RNA base-pairing relationships. • RNA structure prediction: Achieves state-of-the-art performance on secondary structure benchmarks. • 3D RNA folding: Its Zfold adaptation delivers competitive performance with AlphaFold 3 across established RNA structure benchmarks. • Broad generalization: Supports RNA structure prediction, splice-site prediction, IRES identification, and ncRNA classification. The complete dataset, model weights, and source code are openly available. From sequence-only learning to structure-aware foundation models, RNA AI is taking another step forward. Nature paper: doi.org/10.1038/s41586-026-1… #RNA #AIforBiology #FoundationModels #Nature

A new milestone for AI-driven science. Published in Nature, AutoDNA introduces an AI-native experimental laboratory that autonomously designs, executes, and optimizes biomolecular experiments. Powered by multi-agent AI, the system coordinates 20+ types of laboratory instruments and executes over 11,000 hardware operations. Key results: - 97.8% stepwise yield in enzymatic DNA synthesis. - 3.2× faster concurrent experimental execution. - Completed an end-to-end DNA data storage cycle with exact recovery. - Identified and experimentally validated a clinically detected KRAS G13D mutation. From natural language instructions to real-world wet-lab execution, AutoDNA brings AI one step closer to autonomous scientific experimentation. The next generation of AI scientists may not just analyze experiments. They may run the lab themselves. Paper: doi.org/10.1038/s41586-026-1… #AIforScience #AIforBiology #AutonomousLab #Nature