{
  "annotation_id": "8f6368d7-8c19-4a0e-be13-46b60c1d86a4",
  "date_created": "2026-03-02T18:01:35.316000Z",
  "date_modified": "2026-03-02T18:01:35.316000Z",
  "file_hash": "8f4a70d84284e94631fbc79ffe1f7df23b8d2a2fff70cbb8bfdf6eac31148ded",
  "private": false,
  "record": {
    "abstract": "The differential Adhesion Hypothesis (DAH) is a theory of the organization of\ncells within a tissue. In this study we introduce a stochastic model supporting\nthe DAH, that can be seen as a continuous version of a discrete model of Graner\nand Glazier. Our approach is based on the mathematical framework of Gibbsian\nmarked point processes. We provide a Markov chain Monte Carlo algorithm that\ncan reproduce classical biological patterns, and we propose an estimation\nprocedure for a parameter that quantifies the strength of adhesion between\ncells. This procedure is tested through simulations.",
    "arxiv_id": "q-bio/0605035",
    "authors": [
      "Mathieu Emily",
      "Olivier Francois"
    ],
    "categories": [
      "q-bio.TO"
    ],
    "title": "A continuous model for cell sorting",
    "url": "https://arxiv.org/abs/q-bio/0605035"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "48b912f7-c70c-4d68-b115-57aaa897cd1d",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}