{
  "id": 12351344,
  "title": "RI-SINDy: Regulation-Informed Sparse Model Discovery in Biological Gene Networks",
  "url": "https://urgent.news/2026/10/06/ri-sindy-regulation-informed-sparse-model-discovery-in-biological",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-06T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.04.756519v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Oscillatory and saturating dynamics in regulatory gene networks govern processes such as cell cycle timing, circadian rhythms, and inflammatory signaling, and sparse regression methods such as SINDy offer an interpretable method for recovering their governing equations from time-series data. However, these networks are typically governed by Hill-type nonlinearities that become nearly collinear…",
  "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."
}