{
  "id": 17226639,
  "title": "Few-shot regulatory sequence design with a genomic language model",
  "url": "https://urgent.news/2026/10/30/few-shot-regulatory-sequence-design-with-a-genomic-language-model",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-30T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.28.762639v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "A central challenge in generative biology is translating knowledge learned from natural sequences and experiments into designs with desired functions. In-context learning (ICL) is an emergent capability of large language models that allows them to adapt to new tasks from a few examples without additional training, enabling these models to become general-purpose learners. Here, we show that the…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}