{
  "annotation_id": "56e4c7e6-1328-43b5-ab56-b9b1cf1efaf7",
  "date_created": "2026-03-02T18:01:35.572000Z",
  "date_modified": "2026-03-02T18:01:35.572000Z",
  "file_hash": "3923376755823facb2f3763df222fb2bcb837cdfca5ce84e36041cd41a63e422",
  "private": false,
  "record": {
    "abstract": "Biological networks are one of the most studied object in computational\nbiology. Several methods have been developed for studying qualitative\nproperties of biological networks. Last decade had seen the improvement of\nmolecular techniques that make quantitative analyses reachable. One of the\nmajor biological modelling goals is therefore to deal with the quantitative\naspect of biological graphs. We propose a probabilistic model that suits with\nthis quantitative aspects. Our model combines graph with several dynamical\nsources. It emphazises various asymptotic statistical properties that might be\nuseful for giving biological insights",
    "arxiv_id": "q-bio/0702060",
    "authors": [
      "J\u00e9r\u00e9mie Bourdon",
      "Damien Eveillard"
    ],
    "categories": [
      "q-bio.QM",
      "math.PR"
    ],
    "title": "Toll Based Measures for Dynamical Graphs",
    "url": "https://arxiv.org/abs/q-bio/0702060"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8c07e7d9-6f5a-4b17-8098-49badd8454b9",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}