Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and
structure data have radically transformed computational protein design. New methods …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

More than three billion years of evolution have produced an image of biology encoded into
the space of natural proteins. Here we show that language models trained at scale on …

The genome is a sequence that encodes the DNA, RNA, and proteins that orchestrate an
organism's function. We present Evo, a long-context genomic foundation model with a …

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Abstract Machine learning methods for extracting patterns from high-dimensional data are
very important in the biological sciences. However, in certain cases, real-world applications …

Protein language models have shown remarkable success in learning biological information
from protein sequences. However, most existing models are limited by either autoencoding …

RNA plays a pivotal role in translating genetic instructions into functional outcomes,
underscoring its importance in biological processes and disease mechanisms. Despite the …

Directed protein evolution is central to biomedical applications but faces challenges like
experimental complexity, inefficient multi-property optimization, and local maxima traps …

Designing protein mutants with both high stability and activity is a critical yet challenging
task in protein engineering. Here, we introduce PRIME, a deep learning model, which can …