{
  "annotation_id": "65031bd6-a828-4158-9d94-f5928d87bf50",
  "date_created": "2026-03-02T18:01:35.706000Z",
  "date_modified": "2026-03-02T18:01:35.706000Z",
  "file_hash": "ea38b06c6b4d9c82fb1faeef1bc7c1d549b4e13ac9653d4b09337472f0773380",
  "private": false,
  "record": {
    "abstract": "One of the main tasks of post-genomic informatics is to systematically\ninvestigate all molecules and their interactions within a living cell so as to\nunderstand how these molecules and the interactions between them relate to the\nfunction of the organism, while networks are appropriate abstract description\nof all kinds of interactions. In the past few years, great achievement has been\nmade in developing theory of complex networks for revealing the organizing\nprinciples that govern the formation and evolution of various complex\nbiological, technological and social networks. This paper reviews the\naccomplishments in constructing genome-based metabolic networks and describes\nhow the theory of complex networks is applied to analyze metabolic networks.",
    "arxiv_id": "q-bio/0603015",
    "authors": [
      "Jing Zhao",
      "Hong Yu",
      "Jianhua Luo",
      "Z. W. Cao",
      "Yi-Xue Li"
    ],
    "categories": [
      "q-bio.MN"
    ],
    "doi": "10.1007/s11434-006-2015-2",
    "journal_ref": "Chinese Science Bulletin 2006 Vol. 51 No. 13 1529??1537",
    "title": "Complex networks theory for analyzing metabolic networks",
    "url": "https://arxiv.org/abs/q-bio/0603015"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "f9ea3b7f-4145-456d-a051-2966deb4bf1c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}