{
  "id": 8155720,
  "title": "From Prompt to Pipeline: A Comparative Evaluation of Large Language Model Coding Agents for Reproducible Bioinformatics Pipeline Construction",
  "url": "https://urgent.news/2026/09/17/from-prompt-to-pipeline-a-comparative-evaluation-of-large-language",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-17T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.11.751004v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Agentic coding systems are increasingly presented as a way to reduce the engineering burden of scientific software development. Bioinformatics is a strong test case for this claim because useful pipelines must combine domain-specific analysis choices, command-line software, sample metadata, workflow orchestration, container or HPC execution, and interpretable quality-control reporting. We…",
  "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."
}