Genetic Programming and Neural Networks Feedback Linearization for Modeling and Controlling Complex Pharmacogenomic Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{conf/wilf/Floares05,
  title =        "Genetic Programming and Neural Networks Feedback
                 Linearization for Modeling and Controlling Complex
                 Pharmacogenomic Systems",
  author =       "Alexandru Floares",
  year =         "2005",
  editor =       "Isabelle Bloch and Alfredo Petrosino and 
                 Andrea Tettamanzi",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3849",
  booktitle =    "Fuzzy Logic and Applications, 6th International
                 Workshop, WILF 2005, Revised Selected Papers",
  pages =        "178--187",
  address =      "Crema, Italy",
  month =        sep # " 15-17",
  bibdate =      "2006-02-22",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/wilf/wilf2005.html#Floares05",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-32529-8",
  DOI =          "doi:10.1007/11676935_22",
  abstract =     "Modern pharmacology, combining pharmacokinetic,
                 pharmacodynamic, and pharmacogenomic data, is dealing
                 with high dimensional, nonlinear, stiff systems.
                 Mathematical modelling of these systems is very
                 difficult, but important for understanding them. At
                 least as important is to adequately control them
                 through inputs - drugs' dosage regimes. Genetic
                 programming (GP) and neural networks (NN) are
                 alternative techniques for these tasks. We use GP to
                 automatically write the model structure in C++ and
                 optimise the model's constants. This gives insights
                 into the subjacent molecular mechanisms. We also show
                 that NN feedback linearisation (FBL) can adequately
                 control these systems, with or without a mathematical
                 model. The drug dosage regimen will determine the
                 output of the system to track very well a therapeutic
                 objective. To our knowledge, this is the first time
                 when a very large class of complex pharmacological
                 problems are formulated and solved in terms of GP
                 modeling and NN modeling and control.",
  notes =        "Published 2006?",
}

Genetic Programming entries for Alexandru Floares

Citations