Genomics

Research Date: 2026-04-05 Category: AI-Genomics-Gene-Regulation Focus: PARM deep learning model for predicting and designing promoter activity The Bottom Line (TL;DR) Scientists just built an AI that can read and write the “grammar” of gene promoters—the DNA switches that control when and where genes turn on. The model, called PARM (Promoter Activity Regulatory Model), can: ✅ Predict how active a promoter will be in different cell types—just from its DNA sequence ✅ Design custom promoters that work as well as natural ones ✅ Reveal the hidden “rules” of gene regulation that were mysterious for decades Why it matters: This is a major step toward programmable gene expression—think precision gene therapies that activate only in the right cells, or regenerative medicine where we can control exactly which genes turn on during tissue repair. ...

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. ...

Welcome to the first installment of Agentic Omics: When AI Reads the Book of Life. In this 24-part series, we will systematically review the state of the art of Artificial Intelligence (AI) across all major omics disciplines. We will explore how large language models, foundational transformer architectures, and eventually fully autonomous “Agentic Omics” systems are orchestrating domain-specific models to accelerate drug discovery, personalized medicine, and our fundamental understanding of biology. ...