{
  "annotation_id": "e3de10aa-35fd-44f6-bc23-e0c3803d03a6",
  "date_created": "2026-03-02T18:01:35.786000Z",
  "date_modified": "2026-03-02T18:01:35.786000Z",
  "file_hash": "e7fa9e3ebf2bb510d2b27fc8e9196ece51d56ee56fc51d9eb250a24dce2a163a",
  "private": false,
  "record": {
    "abstract": "This paper proposes a new mathematical approach to characterize native\nprotein structures based on the discrete differential geometry of tetrahedron\ntiles. In the approach, local structure of proteins is classified into finite\ntypes according to shape. And one would obtain a number sequence representation\nof protein structures automatically. As a result, it would become possible to\nquantify structural preference of amino-acids objectively. And one could use\nthe wide variety of sequence alignment programs to study protein structures\nsince the number sequence has no internal structure.\n  The programs and this paper with clear figures are available from\nhttp://www.genocript.com.",
    "arxiv_id": "q-bio/0610017",
    "authors": [
      "Naoto Morikawa"
    ],
    "categories": [
      "q-bio.BM",
      "cs.CG",
      "cs.DM",
      "math.MG"
    ],
    "title": "Number sequence representation of protein structures based on the second   derivative of a folded tetrahedron sequence",
    "url": "https://arxiv.org/abs/q-bio/0610017"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "272abef9-7e64-43a5-abd7-9a9ee9172c31",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}