{
  "annotation_id": "be624f18-9d57-446b-899e-e05a812addd5",
  "date_created": "2026-03-02T18:01:35.339000Z",
  "date_modified": "2026-03-02T18:01:35.339000Z",
  "file_hash": "d39fba7c774cba13a1fcc1de3a652e10af8c7142b80c143570d6d99e82e1c0d9",
  "private": false,
  "record": {
    "abstract": "This paper presents efficient algorithms for solving the problem of aligning\na protein structure template to a query amino-acid sequence, known as protein\nthreading problem. We consider the problem as a special case of graph matching\nproblem. We give formal graph and integer programming models of the problem.\nAfter studying the properties of these models, we propose two kinds of\nLagrangian relaxation for solving them. We present experimental results on real\nlife instances showing the efficiency of our approaches.",
    "arxiv_id": "q-bio/0609001",
    "authors": [
      "Nicola Yanev",
      "Rumen Andonov",
      "Philippe Veber",
      "Stefan Balev"
    ],
    "categories": [
      "q-bio.QM"
    ],
    "title": "Lagrangian Approaches for a class of Matching Problems in Computational   Biology",
    "url": "https://arxiv.org/abs/q-bio/0609001"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "da1b855f-4968-4dc0-8d4d-9d6fde0775d1",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}