{
  "id": 4539,
  "url": "https://arxiv.org/abs/2605.10876v1",
  "title": "AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents",
  "summary": "Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational model of cellular behavior that could accelerate biological discovery. One of the most compelling promises of this vision is the ability to perform in silico phenotypic screens, in which a model predicts the effects of cellular perturbations in unseen biological contexts. This task combines heterogeneous textual inputs with diverse phenotypic outpu",
  "authors": "Edward De Brouwer, Carl Edwards, Alexander Wu, Jenna Collier, Graham Heimberg, Xiner Li et al.",
  "category": "research",
  "topics": "agents-autonomy,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-11T17:27:16.000Z",
  "fetched_at": "2026-07-14T16:31:03.580Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4539",
  "original_url": "https://arxiv.org/abs/2605.10876v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}