{
  "abstract": "Functional genomics in crops increasingly depends on integrating information from an extensive literature and heterogeneous multi-omics datasets. Large language models (LLMs) offer a powerful approach to synthesizing these resources and revealing hidden connections across datasets; however, they frequently hallucinate, producing plausible but unsupported claims, when responding to gene-specific queries. Here, we present CucurbitAgent, an AI research agent for functional genomics in the Cucurbitaceae, a major family of horticultural crops. CucurbitAgent integrates multi-omics resources from nine cultivated cucurbit species and more than 18,000 publications, encompassing approximately 256,000 genes, tissue-resolved expression profiles, over 16 million natural genetic variants, and roughly 242,000 predicted protein structures with more than 14 million predicted binding-site residue annotations. Responses link retrieved evidence to source records, including gene entries, expression measurements, structural predictions, and literature passages. On a curated benchmark of 50 tasks assessed by domain experts under blinded conditions, CucurbitAgent achieved an overall pairwise win rate of 96.0% against nine general-purpose LLMs, based on weighted scores for factual accuracy, completeness, relevance, and traceability. The platform is freely available at https://cucurbitagent.com and supports queries in 37 languages collectively spoken by an estimated 70% or more of the world's population. CucurbitAgent not only unifies evidence retrieval and interpretation but also reveals latent associations across datasets, helping researchers formulate testable hypotheses and substantially accelerating candidate-gene research. Its framework is readily transferable to other crops and, more broadly, provides a blueprint for building specialized agents in any domain.",
  "abstract_shown": true,
  "affiliations": [
    "National Engineering Research Center for Vegetables; State Key Laboratory of Vegetable Biobreeding, Beijing Vegetable Research Center, Beijing Academy of Agricu"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "name": "R. Zhang"
    },
    {
      "name": "J. Zhang"
    },
    {
      "name": "Y. Zhang"
    },
    {
      "name": "X. Zhang"
    },
    {
      "name": "J. Yang"
    },
    {
      "name": "C. Xia"
    },
    {
      "name": "J. Zhang"
    },
    {
      "name": "H. Zhao"
    },
    {
      "affs": [
        0
      ],
      "name": "C. Wen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/82217fxkqc1wh.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.09.758138",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.758138v1.full",
  "id": "82217fxkqc1wh",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.758138v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1311|Advances in Cucurbitaceae Research"
    ]
  ],
  "openalex": "W7222813620",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.758138v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/82217fxkqc1wh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:15Z",
      "native_id": "10.64898/2026.10.09.758138",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.09.758138v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "CucurbitAgent: An AI agent for exploring cucurbit multi-omics resources",
  "title_text": "CucurbitAgent: An AI agent for exploring cucurbit multi-omics resources",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:15Z",
  "url": "https://research.draconitic.com/paper/82217fxkqc1wh",
  "venue": "bioRxiv",
  "versions": []
}