{
  "id": 10857548,
  "title": "Disease relevance and replicability of deep learning gene expression prediction",
  "url": "https://urgent.news/2026/09/29/disease-relevance-and-replicability-of-deep-learning-gene-expression",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-29T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.24.753534v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Recent deep learning (DL) models predict average gene expression levels from DNA sequences with high overall correlation to measured values. We examine these DL models through the lens of disease research. The seemingly high overall performance of DL models is largely due to capturing whether genes are \"On\" or \"Off\", and to a lesser extent, disease-relevant expression level changes for \"On\"…",
  "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."
}