{
  "id": 10129019,
  "title": "Heterogeneous Graph Contrastive Learning for Drug-Gene-Disease Motif Prediction",
  "url": "https://urgent.news/2026/09/26/heterogeneous-graph-contrastive-learning-for-drug-gene-disease-motif",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-26T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.21.752883v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Drug repurposing and target discovery offer critical strategies for advancing therapeutic development by uncovering the potential biological pathways and novel associations among drugs, genes, and diseases. However, experimental discovery remains expensive and time-consuming, which limits the scalability of large-scale studies. In addition, existing computational approaches often struggle to…",
  "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."
}