{
  "id": 19777118,
  "title": "sorAI - a suite of machine learning models to predict plant polyploidy from target capture data",
  "url": "https://urgent.news/2026/11/12/sorai-a-suite-of-machine-learning-models-to-predict-plant-polyploidy",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-12T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.11.10.765735v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Premise: Polyploidy is a persistent feature of land plant evolution, yet it is often difficult to determine the ploidy of individual plants. The growing abundance of target capture data and other high-throughput sequence datasets across plant species has generated interest in methods to infer ploidy from these data. We leverage chromosome count data and target capture data from the GoFlag probe…",
  "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."
}