{
  "id": "1710.10637",
  "version": "v1",
  "published": "2017-10-29T16:09:21.000Z",
  "updated": "2017-10-29T16:09:21.000Z",
  "title": "Network translation and steady state properties of chemical reaction systems",
  "authors": [
    "Elisa Tonello",
    "Matthew D. Johnston"
  ],
  "comment": "28 pages",
  "categories": [
    "math.DS"
  ],
  "abstract": "Network translation has recently be used to establish steady state properties of mass action systems by corresponding the given system to a generalized one which is either dynamically or steady state equivalent. In this work we further use network translation to identify network structures which give rise to the well-studied property of absolute concentration robustness in the corresponding mass action systems. In addition to establishing the capacity for absolute concentration robustness, we show that, in contrast to existing results, network translation can often provide a method for deriving the steady state value of the robust species. We furthermore present a MILP algorithm for the identification of translated chemical reaction networks that improves on previous approaches, allowing for easier application of the theory.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-10-29T16:09:21.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "network translation",
      "chemical reaction systems",
      "absolute concentration robustness",
      "steady state equivalent",
      "corresponding mass action systems"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 28,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}