{
  "abstract": "Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.",
  "abstract_shown": true,
  "affiliations": [
    "Fudan University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 26,
  "authors": [
    {
      "name": "B. Dai"
    },
    {
      "name": "Y. Yan"
    },
    {
      "name": "Z. Wang"
    },
    {
      "name": "Y. Liang"
    },
    {
      "name": "S. Li"
    },
    {
      "name": "P. Hu"
    },
    {
      "name": "X. Yang"
    },
    {
      "name": "C. Wang"
    },
    {
      "name": "L. Yi"
    },
    {
      "name": "C. Sun"
    },
    {
      "name": "J. Huang"
    },
    {
      "name": "X. Zhou"
    },
    {
      "name": "H. Chen"
    },
    {
      "name": "D. Zhang"
    },
    {
      "name": "Q. Zou"
    },
    {
      "name": "Y. Du"
    },
    {
      "name": "Z. Hu"
    },
    {
      "name": "Y. Xing"
    },
    {
      "name": "G. Cao"
    },
    {
      "name": "Z. Feng"
    },
    {
      "name": "J. Feng"
    },
    {
      "name": "S. Xu"
    },
    {
      "name": "W. Hu"
    },
    {
      "name": "Y. Zuo"
    },
    {
      "name": "B.-Z. Qian"
    },
    {
      "affs": [
        0
      ],
      "name": "Z. Yuan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ad6cnm28vy7n1.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.01.748536",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1.full",
  "id": "ad6cnm28vy7n1",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1",
  "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",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7208823688",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ad6cnm28vy7n1.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:33Z",
      "native_id": "10.64898/2026.09.01.748536",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Unifying physical and molecular coordinate systems across modalities in spatial biology",
  "title_text": "Unifying physical and molecular coordinate systems across modalities in spatial biology",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:33Z",
  "url": "https://research.draconitic.com/paper/ad6cnm28vy7n1",
  "venue": "bioRxiv",
  "versions": []
}