DNA

The genome is the ultimate source code. For decades, computational biologists have relied on alignment algorithms, hidden Markov models, and specialized machine learning to decode it. Today, a new paradigm is taking hold: DNA foundation models. By treating the genome as a vast, continuous text and training large language models (LLMs) on billions of nucleotides, researchers are teaching AI to “read” the book of life in its native language. In this fifth installment of our Agentic Omics series, we examine the state of the art in genomic AI. We explore how models like DNABERT-2, Nucleotide Transformer, Evo, and HyenaDNA are moving beyond sequence classification to predict gene expression, identify regulatory elements, and quantify variant effects. Crucially, we will dissect the architectural innovations that make this possible—and the biological complexities that still confound these models. ...