{
  "annotation_id": "8060e9ac-1180-47e0-bb40-5250eabe44f3",
  "date_created": "2026-03-02T18:01:31.019000Z",
  "date_modified": "2026-03-02T18:01:31.019000Z",
  "file_hash": "fc2cd89a2303f7b56400159a2ac5a78efc7a70a93bae8bedc9849639ce5dc4b0",
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  "record": {
    "abstract": "This article introduces the physics of information in the context of\nmolecular biology and genomics. Entropy and information, the two central\nconcepts of Shannon\u0027s theory of information and communication, are often\nconfused with each other but play transparent roles when applied to statistical\nensembles (i.e., identically prepared sets) of symbolic sequences. Such an\napproach can distinguish between entropy and information in genes, predict the\nsecondary structure of ribozymes, and detect the covariation between residues\nin folded proteins. We also review applications to molecular sequence and\nstructure analysis, and introduce new tools in the characterization of\nresistance mutations, and in drug design.",
    "arxiv_id": "q-bio/0405004",
    "authors": [
      "Christoph Adami"
    ],
    "categories": [
      "q-bio.BM",
      "q-bio.PE"
    ],
    "doi": "10.1016/j.plrev.2004.01.002",
    "journal_ref": "Physics of Life Reviews 1 (2004) 3-22",
    "title": "Information theory in molecular biology",
    "url": "https://arxiv.org/abs/q-bio/0405004"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "07ab3ab8-4030-4860-82b3-d76ee3d1eb98",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}