{
  "annotation_id": "5e279d5e-d521-4bed-9058-a49f00bf62b2",
  "date_created": "2026-03-02T18:01:35.491000Z",
  "date_modified": "2026-03-02T18:01:35.491000Z",
  "file_hash": "45ca6ade6985a718bfd345dbf3ef378516bc27e6520186b9f7477569ee9e472f",
  "private": false,
  "record": {
    "abstract": "In this paper, we present a survey of the use of graph theoretical techniques\nin Biology. In particular, we discuss recent work on identifying and modelling\nthe structure of bio-molecular networks, as well as the application of\ncentrality measures to interaction networks and research on the hierarchical\nstructure of such networks and network motifs. Work on the link between\nstructural network properties and dynamics is also described, with emphasis on\nsynchronization and disease propagation.",
    "arxiv_id": "q-bio/0604006",
    "authors": [
      "Oliver Mason",
      "Mark Verwoerd"
    ],
    "categories": [
      "q-bio.MN",
      "q-bio.QM"
    ],
    "title": "Graph Theory and Networks in Biology",
    "url": "https://arxiv.org/abs/q-bio/0604006"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "1e5599bf-a8d7-46a8-b412-e34049dbf429",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}