{
  "abstract": "Many complex systems combine dense background structure with sparse contextual information. We introduce a diffusion-based framework for analyzing how sparse condition-specific layers reshape diffusion geometry in multilayer hypergraphs. Each layer is represented as a weighted hypergraph, layers are coupled through shared entities, and random walks on the coupled system induce multiscale diffusion distances between nodes. We apply the framework to disease-conditioned gene networks by coupling a dense MSigDB functional gene-set layer to sparse disease-specific DGIdb drug-gene hypergraphs, with disease-associated drugs selected from DDDB and HumanNet-GSP used to define external gene weights. Across Bipolar Disorder, Schizophrenia, Leukemia, and Breast Cancer, the disease-specific layer contains less than 2 percent of genes in the coupled system, yet substantially changes diffusion distances and community structure. Centrality analysis suggests that this disproportionate effect arises because DGIdb-associated genes occupy influential positions in the MSigDB-derived functional network. The resulting diffusion-derived communities are stable under subsampling and show coherent post hoc functional enrichment, including signaling and neurotransmission categories in neuropsychiatric diseases and immune, translational, and metabolic categories in cancer-associated diseases. Community-level comparisons further reveal disease similarities not reducible to direct DGIdb gene overlap, including a Breast Cancer-Schizophrenia relationship consistent with recent biomedical evidence. These results show that sparse contextual layers can induce interpretable nonlocal changes in higher-order network geometry.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2605.20454",
  "author_total": 2,
  "authors": [
    {
      "name": "Hao Ding"
    },
    {
      "name": "Sanjukta Krishnagopal"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ekgsy1wm32ad6.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2605.20454",
  "fulltext_url": null,
  "id": "ekgsy1wm32ad6",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2605.20454",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.SI"
    ],
    [
      "arxiv",
      "physics.soc-ph"
    ],
    [
      "arxiv",
      "q-bio.QM"
    ],
    [
      "openalex",
      "1312|Bioinformatics and Genomic Networks"
    ]
  ],
  "openalex": "W7161964188",
  "pdf_url": "https://arxiv.org/pdf/2605.20454",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ekgsy1wm32ad6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:50Z",
      "native_id": "2605.20454",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2605.20454"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "arxiv:q-bio.QM",
      "subfield": "bioinformatics"
    },
    {
      "field": "physics",
      "origin": "arxiv:physics.soc-ph",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Sparse Contextual Coupling Reshapes Diffusion Geometry in Multilayer Hypergraphs",
  "title_text": "Sparse Contextual Coupling Reshapes Diffusion Geometry in Multilayer Hypergraphs",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:55Z",
  "url": "https://research.draconitic.com/paper/ekgsy1wm32ad6",
  "venue": "arXiv",
  "versions": []
}