{
  "annotation_id": "ea93d94e-054d-482a-8bbe-f61bcf4d2fb1",
  "date_created": "2026-03-02T18:00:32.682000Z",
  "date_modified": "2026-03-02T18:00:32.682000Z",
  "file_hash": "1cc962d1d5ed0d647d172127d58f0192e3e69fc4dd1d84ad2cc1978801817e7c",
  "private": false,
  "record": {
    "abstract": "Finding out statistically significant words in DNA and protein sequences\nforms the basis for many genetic studies. By applying the maximal entropy\nprinciple, we give one systematic way to study the nonrandom occurrence of\nwords in DNA or protein sequences. Through comparison with experimental\nresults, it was shown that patterns of regulatory binding sites in\nSaccharomyces cerevisiae(yeast) genomes tend to occur significantly in the\npromoter regions. We studied two correlated gene family of yeast. The method\nsuccessfully extracts the binding sites varified by experiments in each family.\nMany putative regulatory sites in the upstream regions are proposed. The study\nalso suggested that some regulatory sites are a ctive in both directions, while\nothers show directional preference.",
    "arxiv_id": "physics/0009002",
    "authors": [
      "Rui Hu",
      "Bin Wang"
    ],
    "categories": [
      "physics.bio-ph",
      "cond-mat.soft",
      "physics.data-an",
      "q-bio"
    ],
    "doi": "10.1016/S0378-4371(00)00488-X",
    "title": "Statistically Significant Strings are Related to Regulatory Elements in   the Promoter Regions of Saccharomyces cerevisiae",
    "url": "https://arxiv.org/abs/physics/0009002"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b12a4623-3b1e-4b78-ac30-3af8120d024f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}