{
  "annotation_id": "284a4aaa-f925-4efe-a5ba-60e679fbaa89",
  "date_created": "2026-03-02T18:01:28.773000Z",
  "date_modified": "2026-03-02T18:01:28.773000Z",
  "file_hash": "c84e17f19af74774ccf912f99ea67eaaa08f84a73e0aae6117579e3397ce95ac",
  "private": false,
  "record": {
    "abstract": "We introduce a random bit-string model of post-transcriptional genetic\nregulation based on sequence matching. The model spontaneously yields a scale\nfree network with power law scaling with $ \\gamma=-1$ and also exhibits\nlog-periodic behaviour. The in-degree distribution is much narrower, and\nexhibits a pronounced peak followed by a Gaussian distribution. The network is\nof the smallest world type, with the average minimum path length independent of\nthe size of the network, as long as the network consists of one giant cluster.\nThe percolation threshold depends on the system size.",
    "arxiv_id": "q-bio/0310027",
    "authors": [
      "Duygu Balcan",
      "Ayse Erzan"
    ],
    "categories": [
      "q-bio.GN"
    ],
    "doi": "10.1140/epjb/e2004-00055-7",
    "title": "Random model for RNA interference yields scale free network",
    "url": "https://arxiv.org/abs/q-bio/0310027"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3ef00cee-57e9-4c2a-a363-e7a8190820ab",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}