{
  "abstract": "Cell fate decisions are shaped by dynamic coordination across transcriptomic, chromatin, and protein layers. Time-series single-cell multi-omics assays now enable these molecular layers to be profiled across developmental stages, yet each cell is still observed only once, and the continuous multi-omics trajectories connecting discrete snapshots remain unresolved. A central challenge is therefore to jointly integrate paired omics measurements while reconstructing their shared developmental progression. Here we present Multi-Omics Fate Inference (MOFI), a dynamically constrained multi-omics integration framework designed to reconstruct continuous cell fate transitions from paired multi-omics snapshots sampled across multiple time points. MOFI jointly models omics-specific state dynamics, cross-omics correspondence, and shared population growth within a unified framework, enabling cross-omics perturbation response analysis and identification of candidate cross-omics transformation programs. Across simulated benchmarks and paired RNA-ATAC/RNA-protein time-series datasets, MOFI reconstructed continuous fate transitions, population dynamics and cross-omics changes consistent with observed measurements. In kidney organoids, MOFI captured coordinated RNA-ATAC progression of nephron lineage specification. In hematopoietic progenitors, MOFI predicted perturbation-responsive lineage redistribution and nominated multi-omics transformation programs linking transcriptional modules with protein-level responses. In neural developmental systems, MOFI resolved gradual brain organoid maturation and interneuron lineage allocation during human cortical development. Together, MOFI provides a dynamics-grounded method for converting discrete paired multi-omics snapshots into interpretable models of cell fate progression, perturbation response, and cross-omics transformation analysis.",
  "abstract_shown": true,
  "affiliations": [
    "Peking University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "J. Shen"
    },
    {
      "name": "Z. Zhang"
    },
    {
      "name": "H. Peng"
    },
    {
      "name": "Q. Peng"
    },
    {
      "name": "Z. Wang"
    },
    {
      "name": "R. Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "P. Zhou"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a05rj5s1ct4jz.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.09.757904",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757904v1.full",
  "id": "a05rj5s1ct4jz",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757904v1",
  "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": "W7222560407",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757904v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/a05rj5s1ct4jz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:11Z",
      "native_id": "10.64898/2026.10.09.757904",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757904v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "MOFI reveals dynamic multi-omics coordination during cell fate progression",
  "title_text": "MOFI reveals dynamic multi-omics coordination during cell fate progression",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:11Z",
  "url": "https://research.draconitic.com/paper/a05rj5s1ct4jz",
  "venue": "bioRxiv",
  "versions": []
}