{
  "id": "1011.1672",
  "version": "v1",
  "published": "2010-11-07T18:54:22.000Z",
  "updated": "2010-11-07T18:54:22.000Z",
  "title": "Separation of time-scales and model reduction for stochastic reaction networks",
  "authors": [
    "Hye-Won Kang",
    "Thomas G. Kurtz"
  ],
  "comment": "49 pages, 18 figures",
  "categories": [
    "math.PR"
  ],
  "abstract": "A stochastic model for a chemical reaction network is embedded in a one-parameter family of models with species numbers and rate constants scaled by powers of the parameter. A systematic approach is developed for determining appropriate choices of the exponents that can be applied to large complex networks. When the scaling implies subnetworks have different time-scales, the subnetworks can be approximated separately providing insight into the behavior of the full network through the analysis of these lower dimensional approximations.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2010-11-07T18:54:22.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "60J27",
      "60J80",
      "60F17",
      "92C45",
      "80A30"
    ],
    "keywords": [
      "stochastic reaction networks",
      "model reduction",
      "time-scales",
      "separation",
      "large complex networks"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 49,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2010arXiv1011.1672K"
    }
  }
}